Allgemein
Handbook of Computational Sciences
THE HANDBOOK OF COMPUTATIONAL SCIENCES IS A COMPREHENSIVE COLLECTION OF RESEARCH CHAPTERS THAT BRINGS TOGETHER THE LATEST ADVANCES AND TRENDS IN COMPUTATIONAL SCIENCES AND ADDRESSES THE INTERDISCIPLINARY NATURE OF COMPUTATIONAL SCIENCES, WHICHREQUIRE EXPERTISE FROM MULTIPLE DISCIPLINES TO SOLVE COMPLEX PROBLEMS.This edited volume covers a broad range of topics, including computational physics, chemistry, biology, engineering, finance, and social sciences. Each chapter provides an in-depth discussion of the state-of-the-art techniques and methodologies used in the respective field. The book also highlights the challenges and opportunities for future research in these areas. The volume pertains to applications in the areas of imaging, medical imaging, wireless and WS networks, IoT with applied areas, big data for various applicable solutions, etc. This text delves deeply into the core subject and then broadens to encompass the interlinking, interdisciplinary, and cross-disciplinary sections of other relevant areas. Those areas include applied, simulation, modeling, real-time, research applications, and more. AUDIENCEBecause of the book’s multidisciplinary approach, it will be of value to many researchers and engineers in different fields including computational biologists, computational chemists, and physicists, as well as those in life sciences, neuroscience, mathematics, and software engineering. AHMED A. ELNGAR, PHD, is the founder and head of Scientific Innovation Research Group (SIRG) and assistant professor of Computer Science at the Faculty of Computers and Information, Beni-Suef University, Egypt. VIGNESHWAR. M., is head of R & D and Academic Initiatives, Cybase Technologies, Coimbatore, Tamil Nadu, India. He has around 9 years in industry & research and 8 years in academia. He has an M.E., degree in computer science and engineering, and has published more than 110 international/national conference and journal publications as well as numerous awards. KRISHNA KANT SINGH, PHD, is an associate professor in the Faculty of Engineering & Technology, Jain (Deemed-to-be University), Bengaluru, India. Dr. Singh has acquired BTech, MTech, and PhD (IIT Roorkee) in the area of machine learning and remote sensing. He has authored more than 50 technical books and research papers in international conferences and SCIE journals. ZDZISLAW POLKOWSKI, PHD, is a professor in the Faculty of Technical Sciences, Jan Wyzykowski University, Polkowice, Poland. He has published more than 75 research articles in peer-reviewed journals.
Innovative Engineering with AI Applications
INNOVATIVE ENGINEERING WITH AI APPLICATIONSINNOVATIVE ENGINEERING WITH AI APPLICATIONS DEMONSTRATES HOW WE CAN INNOVATE IN DIFFERENT ENGINEERING DOMAINS AS WELL AS HOW TO MAKE MOST BUSINESS PROBLEMS SIMPLER BY APPLYING AI TO THEM.Engineering advancements combined with artificial intelligence (AI), have resulted in a hyper-connected society in which smart devices are not only used to exchange data but also have increased capabilities. These devices are becoming more context-aware and smarter by the day. This timely book shows how organizations, who want to innovate and adapt, can enter new markets using expertise in various emerging technologies (e.g. data, AI, system architecture, blockchain), and can build technology-based business models, a culture of innovation, and high-performing networks. The book specifies an approach that anyone can use to better architect, design, and more effectively build things that are technically novel, useful, and valuable, and to do so efficiently, on-time, and repeatable. AUDIENCEThe book is essential to AI product developers, business leaders in all industries and organizational domains. Researchers, academicians, and students in the AI field will also benefit from reading this book. ANAMIKA AHIRWAR, PHD, is an associate professor at the Compucom Institute of Information Technology & Management, Jaipur, India. She has about 20 years of experience in teaching and research and has published more than 45 research papers in reputed national/international journals and conferences, authored several books as well as five patents. PIYUSH KUMAR SHUKLA, PHD, is an associate professor in the Department of Computer Science & Engineering, University Institute of Technology, Bhopal, India. He has about 15 years of experience in teaching and research, is the author of 3 books, more than 50 articles and book chapters in international publications, as well as 15 Indian patents. MANISH SHRIVASTAVA, PHD, is the Principal of the Chameli Devi Institute of Technology & Management, Indore, India. He has published more than 100 articles in international journals and spent 7 years as a software engineer. PRITI MAHESHWARY, PHD, is a professor in the Department of CSE and Head of the Centre for Excellence in Internet of Things and Advance Computing Lab, Rabindranath Tagore University, Bhopal, India. BHUPESH GOUR, PHD, is a professor in the Department of Computer Science and Engineering at Lakshmi Narain College of Technology in Bhopal, India. He has 22 years of experience in academia as well as the software industry. He has published more than 50 articles in national and international journals, as well as four patents.
Pro T-SQL 2022
Learn how to write and design simple and efficient T-SQL code. This is a hands-on book that teaches you how to write better T-SQL with examples and straightforward explanations. New in this edition is coverage of Parameter Sensitive Plan (PSP) optimization, Azure Synapse Link for real-time analytics, integration with S3-compatible object storage, and SQL Ledger tables based on blockchain. You’ll learn to improve your T-SQL design in ways that provide faster performance, stronger security, and easier comprehension. The book identifies common anti-patterns in writing T-SQL and instructs you on how to change your code so you can be more confident in writing T-SQL code that is reliable and performs well.Pro T-SQL 2022 is focused on the problems that developers are faced with and must solve in delivering successful applications. The content begins from a foundation of writing T-SQL that is clear and understandable. The book then takes you through writing SQL that performs well, is easy to manage through coding standards and version control, can be maintained and modified as business requirements change over time, scales as your business grows, and takes advantage of the full range of security features built into the SQL Server and Azure SQL database engines.WHAT YOU WILL LEARN* Choose the correct data types and database objects when designing your T-SQL* Write T-SQL that accesses your data efficiently and uses hardware effectively* Implement source control and testing methods to streamline your deployment process.* Design T-SQL that is flexible and can be enhanced or modified with little effort* Plan for long-term data management, including growth and purging of older data* Enhance database security through features such as encryption, data masking, row-level security, and the SQL Ledger blockchain table typeWHO THIS BOOK IS FORDatabase developers who want to improve the efficiency of their applications with better T-SQL; developers who want to know more about T-SQL so they can be prepared to solve complex problems more easily; data professionals who want to write high-quality T-SQL that performs well, is flexible to changing needs, and is easy for others to understandELIZABETH NOBLE is a Microsoft Data Platform MVP and Director of Database Development in the metro Atlanta area. When ze was introduced to hir first database over 10 years ago, ze found the career ze wanted to pursue. Hir passion is to help others improve the quality and speed of deploying database changes through automation. When ze is not trying to automate database development, ze can be found spending time with zir dogs, painting, paddle boarding, or throwing axes. IntroductionPART I. BUILDING UNDERSTANDABLE T-SQL1. Data Types2. Database Objects3. Standardizing T-SQL4. Designing T-SQLPART II. BUILDING PERFORMANT T-SQL5. Set-Based Design6. Hardware Usage7. Execution Plans8. Optimize T-SQLPART III. BUILDING MANAGEABLE T-SQL9. Coding Standards10. Source Control11. Testing12. DeploymentPART IV. BUILDING MAINTAINABLE T-SQL13. Functional Design14. Logging15. EnhancementPART V. BUILDING SCALABLE T-SQL16. Managing Data Growth17. Managing Data Long TermPART VI. BUILDING SECURE T-SQL18. Implementing Security Features19. Implementing Encryption
Technology Assessment of Dual-Use ICTs
Information and Communication Technologies (ICTs) are important to human, national, and even international security. IT research, artifacts, and knowledge that can be applied in military and civilian contexts, used as part of weapon systems, or cause significant harm are referred to as dual-use. Advances in artificial intelligence (AI), robotics, cybersecurity, and open source intelligence (OSINT) raise questions about their dual-use risks. But how can dual-use of such disparate technologies be assessed? Case studies are still lacking on how to assess dual-use ICT and how to enable sensitive and responsible dual-use design. To address the research gap, this cumulative dissertation uses Technology Assessment (TA) as an epistemological framework to bring together approaches of Critical Security Studies (CSS) as well as Value Sensitive Design (VSD) from the field of Human-Computer Interaction (HCI). As a result, the dissertation systematizes the dual-use risks and scenarios of the selected ICTs and derives organizational and design implications.ABOUT THE AUTHOR:THEA RIEBE is a post-doctoral researcher at the Chair of Science and Technology for Peace and Security (PEASEC) in the Department of Computer Science at the TU Darmstadt. She did her interdisciplinary PhD on technology assessment of dual-use technologies in computer science, combining approaches from critical security research, and human-computer interaction. Introduction.- Theoretical Background and Related Work.- Research Design.- Results.- Discussion.- Conclusion.- Measuring Spillover Effects from Defense to Civilian Sectors: A Quantitative Approach Using LinkedIn.- Dual-Use and Trustworthy? A Mixed Methods Analysis of AI Diffusion between Civilian and Defense R&D.- Meaningful Human Control of LAWS: The CCW-Debate and its Implications for Value-Sensitive Design.- U.S. Security Policy: The Dual-Use Regulation of Cryptography and its Effects on Surveillance.- Values and Value Conflicts in the Context of OSINT Technologies for Cybersecurity Incident Response.- Computer Emergency Response Teams and the German Cyber Defense: An Analysis of CERTs on Federal and State Level.- Privacy Concerns and Acceptance Factors of OSINT for Cybersecurity: A Representative Survey.- CySecAlert: An Alert Generation System for Cyber Security Events Using Open Source Intelligence Data.- Bibliography.
Domain Storytelling
Fachliche Anforderungen in der Softwareentwicklung: Verstehen und verstanden werden- fachliche motivierte Grenzen in Domänen finden, um Software und Teams danach zu organisieren- Anforderungen aus Domain Stories ableiten- Domain Storytelling mit Event Storming, User Story Mapping und anderen Methoden der agilen Softwareentwicklung kombinierenGeschichtenerzählen ist tief in der menschlichen Kommunikation verankert – das gilt auch im Zeitalter der Software. "Fachliche Geschichten" zu erzählen und zu visualisieren macht Geschäftsprozesse und Fachwissen greifbar.Dieses Buch zeigt, wie Sie mit einfachen Mitteln fachlich stimmige Anwendungssoftware entwickeln können. Domain Storytelling hilft, das Fachwissen aus den Köpfen der Anwender*innen in die Köpfe von Entwickler*innen, Product Owners, Produktmanagement und Business Analysts zu transportieren. Es bringt die Beteiligten in Workshops zusammen, um sich über Aufgaben und Prozesse im Unternehmen abzustimmen. Das Ergebnis wird in einer einfachen Bildsprache dokumentiert.Die Autoren erläutern an verständlichen Beispielen, wie Domain Storys entstehen und wie man Domain Storytelling für Domain-Driven Design, die Anforderungsermittlung und weitere Zwecke einsetzen kann.Stefan Hofer hat in Österreich Software Engineering studiert und einen Doktortitel in Informatik an der Universität Hamburg erworben. Seit 2005 arbeitet er für die WPS – Workplace Solutions GmbH. Requirements Enginee-ring und Domain-Driven Design bilden seine Themenschwerpunkte. Stefan ist auf Mastodon (@hofstef@social.wps.de), Twitter (@hofstef) und per E-Mail (stefan@domainstorytelling.org) erreichbar. Henning Schwentner beschäftigt sich mit Computern, seit er Anfang der 90er-Jahre einen Amiga 500 zum Geburtstag bekam. Er hatte das Glück, diese Leidenschaft zum Beruf zu machen, und arbeitet als Coder, Coach und Consultant bei WPS – Workplace Solutions. Er hilft Teams dabei, Struk-tur in ihre bestehende Software zu bringen oder neue Systeme mit einer nachhaltigen Architektur von Grund auf aufzubauen. Henning ist der Au-tor von Domain-Driven Transformation und LeasingNinja.io, der Übersetzer von Domain-Driven Design kompakt und Mitorganisator des ComoCamps. Er schreibt im Fediverse als @hschwentner@social.wps.de, twittert als @hschwentner und liest E-Mails, die an henning@domainstorytelling.org ge-richtet sind. Henning ist stolzer Vater von sechs Kindern in einer ganz be-sonderen Patchwork-Situation.
Praxishandbuch Terraform
Erprobtes Praxiswissen für die Infrastruktur-Provisionierung mit Terraform- International bekanntes Standardwerk in der 3. Auflage - von Mitchell Hashimoto, dem Entwickler von Terraform und Mitbegründer von HashiCorp empfohlen- Vermittelt über grundlegende Funktionen hinaus Patterns und Best Practices; inklusive Hilfestellungen zum Testen, zur Wiederverwendbarkeit von Code oder zu Team-Workflows.- Niedrigschwelliges Ausprobieren der Codebeispiele durch Open-Source-Beispiele auf GitHub und AWS umfangreiches Trial-Angebot.Terraform hat sich in der DevOps-Welt zu einem Schlüsselwerkzeug entwickelt. Es ermöglicht Mitarbeiter:innen in DevOps, Administration und Entwicklung, IT-Infrastruktur mithilfe von Code und Skripten für eine Vielzahl von Cloud- und Virtualisierungsplattformen wie AWS, Google Cloud Plattform, Azure u.v.a. zu definieren, bereitzustellen und zu managen.Die Übersetzung der dritten Auflage zeigt Ihnen den schnellstmöglichen Einstieg, um mit Terraform loszulegen. Yevgeniy (Jim) Brikman, Mitbegründer von Gruntwork, demonstriert anhand von aussagekräftigen Codebeispielen, wie Sie mit der einfachen, deklarativen Programmiersprache von Terraform das Bereitstellen und das Managen von IT-Infrastruktur mit nur wenigen Befehlen umsetzen. Mit diesem Praxishandbuch eignen sich erfahrene Sysadmins, DevOps Engineers, aber auch Entwickler:innen belastbare Terraform-Grundlagen an. Sie werden in kurzer Zeit den Betrieb eines vollständigen IT-Stacks – auch bei massivem Datenaufkommen oder für ein großes Entwicklerteam – erfolgreich bewältigen.Yevgeniy (Jim) Brikman ist Mitbegründer der Firma Gruntwork, das sich das Ziel gesetzt hat, die Erstellung von Software zehnmal einfacher zu machen. Er ist mehrfacher Autor und war als Software-Engineer bei LinkedIn, TripAdvisor, Cisco und Thomson Financial tätig. Weitere Informationen finden Sie unter ybrikman.com.
Optimierungsmethoden
Das Buch gibt eine breite Übersicht über die wichtigsten Optimierungsmethoden, wobei die Verfahren beispielhaft erläutert und mit über 400 Abbildungen illustriert werden. Im ersten Teil des Buches werden verschiedene Klassen von Optimierungsproblemen vorgestellt. Gegenstand des zweiten Teils sind klassische Methoden zur Lösung von Optimierungsproblemen. Im dritten Teil werden naturanaloge Optimierungsmethoden behandelt, darunter physikbasierende Algorithmen, evolutionäre Algorithmen, schwarmintelligente Methoden sowie Optimierungsverfahren, die durch das Immunsystem inspiriert sind. Der letzte Teil des Buches befasst sich mit der Optimierung neuronaler Netze und gibt eine Einführung in ein neues vielversprechendes Forschungsgebiet der KI-basierten, selbstlernenden Optimierungsalgorithmen. PROF. DR. RALF HOLLSTEIN lehrte an der Universität Paderborn und bis zu seiner Emeritierung an der TH Bingen im Bereich Mathematik und Computational Intelligence. Klassen von Optimierungsproblemen - Klassische Optimierungsmethoden - Naturanaloge Optimierungen - Optimierung von neuronalen Netzen - Neuronale kombinatorische Optimierung
Digital Transformation and Public Policies
The extent of digitalization and the use of digital tools no longer need to be demonstrated. While companies have been integrating the challenges of such a transformation for more than 20 years, the public sector is lagging behind.Digital Transformation and Public Policies studies the mechanisms of the digital transformation of public organizations. It explores how this new deal, driven mainly by platforms, resonates with new public policies and how digital technology is redrawing the relationship between the governors and the governed.This book, the result of transdisciplinary collaboration between researchers, aims to answer these questions by focusing on several cases: public innovation policies, health data and social policies with fiscal microsimulation devices. Valérie Revest is Professor of Economics at the Université Jean Moulin Lyon 3, iaelyon School of Management – Magellan, France. Her research focuses on the financing of innovation, digital platforms and the transformation of public innovation policies.Isabelle Liotard is a lecturer in economics at the Université Sorbonne Paris Nord – CEPN, France. Her research focuses on the digital economy, innovation and the effects of digital transformation on companies and the public sector.
Cybercrime During the SARS-CoV-2 Pandemic
The SARS-CoV-2 pandemic has had an undeniable impact on cybercrime. The initial crisis quickly became a global catastrophe with multiple consequences in economics, health, and political and social fields. This book explores how this global emergency has influenced cybercrime. Indeed, since feeding off new vulnerabilities, thanks to the effects of the pandemic crisis in various states around the world, cybercrime has increased and evolved.In 2020, the world was already dealing with numerous tensions and the effects of the global crisis have therefore only tended to exacerbate the issues that relate to cybercrime. For example, radicalization and identity theft has found an environment in which they thrive: the Internet. Criminals have been able to adapt their modus operandi, their targets and their attack vectors. However, on the plus side, the response of law enforcement and public authorities, in terms of the legal, policing and policy side of cybercrime, has also been adapted in order to better combat the increase in this phenomenon. Daniel Ventre has a PhD in Political Science and conducts his research at the CESDIP laboratory, CNRS, Université Paris Saclay, France. His work focuses on cybersecurity and cyberdefense policies.Hugo Loiseau has a PhD in Political Science and is a professor at l’École de politique appliquée at the Université de Sherbrooke, Canada. His research focuses on the political and international issues involving cybersecurity.
Google Cloud Platform (GCP) Professional Cloud Network Engineer Certification Companion
While many guides exist to help software engineers learn cloud networking design and architecture concepts, and even prepare for cloud network certifications on AWS and Azure, far fewer resources are available covering the Google Cloud Platform (GCP) Professional Cloud Network Engineer certification exam. Well, look no further! This self-paced guide book is designed to help engineers learn cloud networking best practices on GCP, and prepare for the GCP Professional Cloud Network Engineer certification exam.You will waste no time when you use this study companion. It lets you dive in and learn how GCP differs from other public cloud providers (AWS and Microsoft Azure). You will understand GCP's unique ability to allow virtual private clouds (VPCs) that span across multiple regions. You will know how to leverage GCP as a competitive advantage in the IT engineering community. Key concepts covered on the exam are called out and applied in each chapter of this book, giving you both practice and reinforcement, a far more effective learning tool than rote learning or similar approaches typically enlisted in exam preparation.Enterprises are looking for developers with Google networking skills. Now is the time to skill up! This book shows you how to leverage GCP’s developer-focused, user-friendly approach to understand how the networking components enabling the popular 1B-user Google products (e.g., Gmail, Google Search, YouTube, Google Workspace (formerly G-Suite), Google Maps, Google Photos, and many others) work behind the scenes.WHAT YOU WILL LEARNIn addition to preparing for the GCP Professional Cloud Network Engineer certification exam, you will learn how to:* Architect and design a virtual private cloud* Implement a virtual private cloud* Configure network services* Implement hybrid connectivity* Implement network security* Manage network operations* Optimize network resourcesWHO THIS BOOK IS FORSoftware engineers (network, DevOps, SecOps, DataOps, engineers skilled with SDLC), software architects (solution, security, data, infrastructure, cloud, those skilled with TOGAF), and IT professionals. Prerequisites: While this study companion is intended to be self-contained, a basic knowledge of cloud computing along with hands-on experience with a minimum of two modern programming languages (Java, C#) is beneficial in order for readers to fully achieve the objectives of the book.DARIO CABIANCA is a computer scientist (PhD, University of Milan), author, and Cloud Architect. He has worked with a variety of global enterprises for more than two decades and possesses more than 11 cloud certifications. He used his own fail-proof techniques to prepare and pass GCP, Azure, and AWS exams. He is excited to share his knowledge to help readers of his study companion book prepare for the GCP Professional Cloud Network Engineer certification exam, and also come away equipped with the necessary tools and knowledge to be confident and successful on the job.1. Exam Overview1.1. Exam Subject Areas1.2. Exam Format1.3. Supplemental Study Materials1.4. Sign up for a Free Tier1.5. Register for the Exam1.5.1. Schedule the Exam1.5.2. Rescheduling and Cancellation Policy1.5.3. Exam Results1.5.4. Retake Policy1.6. Summary2. Designing, planning, and prototyping a Google Cloud network2.1. Designing an overall network architecture2.1.1. High availability, failover, and disaster recovery strategies2.1.2. DNS strategy (e.g., on-premises, Cloud DNS)2.1.3. Security and data exfiltration requirements2.1.4. Load balancing2.1.5. Applying quotas per project and per VPC2.1.6. Hybrid connectivity (e.g., Google private access for hybrid connectivity)2.1.7. Container networking2.1.8. SaaS, PaaS, and IaaS services2.2. Designing Virtual Private Cloud (VPC) instances2.2.1. VPC Specifications2.2.2. Subnets2.2.3. IP address management and brin your own IP (BYOIP)2.2.4. Standalone vs. Shared VPC2.2.5. Multiple vs. single2.2.6. Regional vs. multi-regional2.2.7. VPC Network Peering2.2.8. Firewalls (e.g., service account-based, tag-based)2.2.9. Custom routes2.3. Designing a hybrid and multi-cloud network2.3.1. Drivers for Hybrid and Multi-cloud strategy2.3.2. Overall goals2.3.3. Designing a Hybrid and Multi-cloud strategy2.3.4. Dedicated Interconnect vs. Partner Interconnect2.3.5. Direct vs. Carrier Peering2.3.6. IPsec VPN2.3.7. Bandwidth and constraints provided by hybrid connectivity solutions2.3.8. Cloud Router2.3.9. Multi-cloud and Hybrid topologies2.3.10. Regional vs. global VPC routing mode2.3.11. Failover and Disaster Recovery strategy2.3.12. Accessing Google Services/APIs privately from on-premises locations2.3.13. IP address management across on-premises locations and cloud2.4. Designing an IP addressing plan for Google Kubernetes Engine2.4.1. GKE VPC-native clusters2.4.2. Optimizing GKE IP ranges2.4.3. Expanding GKE IP ranges2.4.4. Public and private cluster nodes2.4.5. Control plane public vs. private endpoints2.5. Summary2.6. Exam questions3. Implementing Virtual Private Cloud (VPC) instances3.1. Configuring VPC resources3.1.1. Creating VPCs3.1.2. Creating subnets3.1.3. Listing subnets3.1.4. Listing VPCs3.1.5. Deleting VPCs3.2. Configuring VPC Network Peering3.3. Creating a Shared VPC network and sharing subnets with other projects3.3.1. Host and service project concepts3.3.2. Shared VPC deep dive3.3.3. Assigning roles to principals3.3.4. Creating the shared VPC3.3.5. Creating the service projects3.3.6. Enabling Compute API for service and host projects3.3.7. Enabling host project3.3.8. Attaching service projects3.3.9. Assigning individual subnet-level roles to service projects3.4. Using a Shared VPC3.4.1. Listing usable subnets3.4.2. Creating VMs3.4.3. Verifying VMs connectivity3.4.4. Deleting VMs3.5. Sharing subnets using folders3.6. Configuring API access to Google services (e.g., Private Google Access, public interfaces)3.6.1. Configuring Private Google Access (PGA)3.6.2. Configuring Private Service Connect (PSC)3.7. Expanding VPC subnet ranges after creation3.8. Configuring routing3.8.1. Static vs. dynamic routing3.8.2. Global vs. regional dynamic routing3.8.3. Routing policies using tags and priority3.8.4. Internal load balancer as a next hop3.8.5. Custom route import/export over VPC Network Peering3.9. Configuring and maintaining Google Kubernetes Engine clusters. Considerations include:3.9.1. VPC-native clusters using alias IPs3.9.2. Clusters with Shared VPC3.9.3. Creating Cluster Network Policies3.9.4. Private clusters and private control plane endpoints3.9.5. Adding authorized networks for cluster control plane endpoints3.10. Configuring and managing firewall rules. Considerations include:3.10.1. Target network tags and service accounts3.10.2. Rule priority3.10.3. Protocols and Ports3.10.4. Direction3.10.5. Firewall rule logs3.10.6. Summary4. Implementing VPC Service Controls4.1. Creating and configuring access levels and service perimeters4.2. Service perimeter deep dive4.3. VPC accessible services4.4. Perimeter bridges4.5. Audit logging4.6. Dry run mode4.7. Dry-run perimeter deep dive4.8. Exam questions5. Configuring load balancing5.1. Google Cloud load balancers family5.2. Backend services and network endpoint groups (NEGs)5.3. Firewall rules to allow traffic and health checks to backend services5.4. Health checks for backend services and target instance groups5.5. Configuring backends and backend services with balancing method (e.g., RPS, CPU, Custom), session affinity, and capacity scaling/scaler5.6. TCP and SSL proxy load balancers5.7. Load balancers (e.g., External TCP/UDP Network Load Balancing, Internal TCP/UDP Load Balancing, External HTTP(S) Load Balancing, Internal HTTP(S) Load Balancing)5.8. Protocol forwarding5.9. Accommodating workload increases using autoscaling vs. manual scaling5.10. Configuring Google Cloud Armor policies. Considerations include:5.11. Security policies5.12. Web application firewall (WAF) rules (e.g., SQL injection, cross-site scripting, remote file inclusion)5.13. Attaching security policies to load balancer backends5.14. Configuring Cloud CDN. Considerations include:5.15. Enabling and disabling5.16. Cloud CDN5.17. Cache keys5.18. Invalidating cached objects5.19. Signed URLs5.20. Custom origins6. Configuring advanced networking services6.1. Configuring and maintaining Cloud DNS6.1.1. Managing zones and records6.1.2. Migrating to Cloud DNS6.1.3. DNS Security Extensions (DNSSEC)6.1.4. Forwarding and DNS server policies6.1.5. Integrating on-premises DNS with Google Cloud6.1.6. Split-horizon DNS6.1.7. DNS peering6.1.8. Private DNS logging6.2. Configuring Cloud NAT6.2.1. Addressing6.2.2. Port allocations6.2.3. Customizing timeouts6.2.4. Logging and monitoring6.2.5. Restrictions per organization policy constraints6.3. Configuring network packet inspection6.3.1. Packet Mirroring in single and multi-VPC topologies6.3.2. Capturing relevant traffic using Packet Mirroring source and traffic filters6.3.3. Routing and inspecting inter-VPC traffic using multi-NIC VMs (e.g., next-generation firewall appliances)6.3.4. Configuring an internal load balancer as a next hop for highly available multi-NIC VM routing7. Implementing hybrid interconnectivity7.1. Configuring Cloud Interconnect7.1.1. Dedicated Interconnect connections and VLAN attachments7.1.2. Partner Interconnect connections and VLAN attachments7.2. Configuring a site-to-site IPsec VPN7.2.1. High availability VPN (dynamic routing)7.2.2. Classic VPN (e.g., route-based routing, policy-based routing)7.3. Configuring Cloud Router7.3.1. Border Gateway Protocol (BGP) attributes (e.g., ASN, route priority/MED, link-local addresses)7.3.2. Custom route advertisements via BGP7.3.3. Deploying reliable and redundant Cloud Routers8. Managing network operations8.1. Logging and monitoring with Google Cloud’s operations suite8.1.1. Reviewing logs for networking components (e.g., VPN, Cloud Router, VPC Service Controls)8.2. Monitoring networking components (e.g., VPN, Cloud Interconnect connections and interconnect attachments, Cloud Router, load balancers, Google Cloud Armor, Cloud NAT)8.3. Managing and maintaining security8.4. Firewalls (e.g., cloud-based, private)8.5. Diagnosing and resolving IAM issues (e.g., Shared VPC, security/network admin)8.6. Maintaining and troubleshooting connectivity issues8.6.1. Draining and redirecting traffic flows with HTTP(S) Load Balancing8.6.2. Monitoring ingress and egress traffic using VPC Flow Logs8.6.3. Monitoring firewall logs and Firewall Insights8.6.4. Managing and troubleshooting VPNs8.6.5. Troubleshooting Cloud Router BGP peering issues8.7. Monitoring, maintaining, and troubleshooting latency and traffic flow8.8. Testing network throughput and latency8.9. Diagnosing routing issues8.10. Using Network Intelligence Center to visualize topology, test connectivity, and monitor performance
Enhancing Adobe Acrobat Forms with JavaScript
Take your PDF forms to the next level! In this book, you’ll learn various ways to further improve your PDF forms using simple JavaScript coding. You’ll also discover how a few lines of code can speed up your workflow when working with multiple PDFs in Action Wizard.Enhancing Adobe Acrobat Forms with JavaScript covers up-to-date, real working examples that you can easily download and practice with and edit to suit your own projects. This book also shows workarounds and solutions to various form issues you might encounter. Feel empowered by it and improve your PDF documents!JavaScript has been a part of Adobe Acrobat for many versions. However, few people use its features and focus mainly on using basic form properties, never delving deeper into Acrobat’s full capabilities. While information on the web can be helpful, if you don’t know enough about how to use JavaScript in Acrobat you will be left with poor results. JavaScript can be difficult to learn, but it does not need to be scary. This book explains in simple steps for beginner to intermediate level so that you can take full advantage of Acrobat’s capabilities for your own projects.WHAT YOU WILL LEARN• Learn simplified field notation and basic JavaScript for Acrobat• Work with buttons that can be used for navigation• Improve form navigation and printing of forms• Add various types of alerts and custom validations to improve client-entered-data• Learn the basics of how to prepare a form for e-signingWHO IS THIS BOOK FORThis book is for anyone who needs to create forms for clients or websites. Students, lawyers, accountants, and human resources will be able to take their work to the next level by streamlining their workflow and utilizing advanced JavaScript features in Adobe Acrobat.Jennifer Harder has worked in the graphic design industry for over fifteen years. She has a degree in graphic communications and is currently teaching Acrobat, and Adobe Creative Cloud courses at Langara College. She is also author of several Apress books and related videos.Part 1: Basic Form ImprovementsChapter 1: A Fundamental Forms PrimerSub -Topics:• Forms Review• Fields Refresher• Properties Refreshero Text Box Field Properties and New Date Field Propertieso Dropdown Propertieso List Box Propertieso Check Box Propertieso Radio Button Propertieso Button Properties and Image Propertieso Digital Signature Propertieso Barcode Properties• Tab Properties Refresher• Setting Field Tab Order using the menu options• Clearing a Form while workingChapter 2: Introduction to ActionsSub – Topics:• Getting Started• Rating Forms Value Averaging and Sum: Working with Text Fieldso The Validate Tab• Page 2 of Project: The Calculate Tab for the Grand Total Using Sum• Sum and Averaging Using Check Boxes or Radio Buttons with Text Fieldso Using Radio Buttons on Page 3 of the Projecto Using Check Boxes on Page 3 of the Projecto Learning how check boxes can become radio buttons• Basic Action Button Triggers for Reset Buttons and Printing Buttonso Reset Buttono Print Form ButtonChapter 3: Creating a QR Code Custom StampSub - Topics:• Customizing Your QR Code Stamp• QR Code Creation• Using the Stamp Tool• Final Thoughts: QR Code for Professional PrintingChapter 4: Buttons, Navigation, Form and Non-Form ActionsSub - Topics:• Creating a Button Icono Example of a Button as a Label Only• Non-Form Properties Actionso Pageso Bookmarkso Web Hyperlinkso Rich Media Non-Form Navigation Buttonso Layers Basic Actionso Other Non-Form Actions• Triggers for Actions• Choose an Action That Requires No Code• Newsletter Navigation with Buttons• Form Navigation with a Button as Helpful Hint• Adding a Comb of Characters• Before Comb and After Comb• More Action Triggers to Show and Hideo Hide and Clear Fields Button• Set Layer Visibilityo Using Bookmarkso Using ButtonsPart 2: Simplified Field Notation and Basic JavaScriptChapter 5: Introduction to Simplified Field Notation and JavaScriptSub - Topics:• Getting Started• Text Field, Date, and Dropdown Menu Propertieso Action Tabo Format Tabo Validate Tabo Calculate Tabo Check Box, Radio Button, Image Field, and Button Propertieso List Box Propertieso Digital Signature Propertieso Barcode Propertieso Global Document JavaScripto Web Links and Referenceso Regular Forms vs. E-Sign Forms• JavaScript and Acrobat on the Document LevelChapter 6: Basic and Complex CalculationsSub - Topics:• Getting Started• Sum Value• Simplified Field Notation• JavaScript Custom Calculation Script• Resetting Your Field of Focus• Final Thoughtso The Final Line of Code (Setting the 0 value to blank)o Dropdown AlternativesChapter 7: Format CalculationsSub - Topics:• Number Formatting• Formatting with a Percentageo A Workaround for the Percentage• Date Formatting• Time Formatting• Final Thoughtso Dropdown AlternativesChapter 8: Various JavaScript Alerts, Notes and Time StampsSub - Topics:• Alert Types• Create a Document JavaScript• Viewer Version and Validation Alert• Document Actionso Document Will Closeo Document Will Print• Alerts Working with Buttons• Adding a Comment Note, Signature, and Time StampChapter 9: Create Help for Clients with Rollover Text and AlertsSub - Topics:• The Rollover Methodo Mouse Entero Mouse Exito Extra Non-Custom JavaScript Check Box Exampleo How to Show, Hide Fields with JavaScript• The Default Text Method• The Alert Methodo Customer’s Full Nameo Dateo Customer Order Codeo Customer’s Company Name• How to Duplicate Text for multiple fields and make fields read only with JavaScript• Final ThoughtsChapter 10: Various Types of Formatting with JavaScriptSub - Topics:• Adding Global Formatting to Text Fields• Color Properties• Multi-Line Buttons• Multi-Line Text• Complex Formatting Using Check Boxes and Text Fields• Rich Text Formatting for Text Fields and Comments• Silent Printing• Options for Submit Button using email• Final ThoughtsPart 3: Working with More Complex FormsChapter 11: Validation with Text Boxes, Alerts and Radio ButtonsSub - Topics:• Money Transfer Example• Changing the Shipping Price Using Radio Buttons• Additional Checkbox and Radio Button examples with JavaScript and Text Fields and how to change data.• Text Field Validation with Regular Expressionso Telephone Validationo Name Validationo Account Number Validationo Email and URL Validationo Another Phone and Date Example with Two Variables• Final ThoughtsChapter 12: Working with Dropdown MenusSub - Topics:• Current Skills Request Form• Parts Order Form• Final Thoughtso Load a Lengthy Single Dropdown or List MenuChapter 13: Working with List BoxesSub - Topics:• List Box Priority List with Control Buttonso The Add Buttono The Delete Buttono The Clear or Reset Buttono The Up Buttono The Down Button• Check Box, Dropdown, and List Box Example 1• Check Box, List Box, and Multi-Dropdown Example 2• Button Slide Show Variationo Extra Example Priority List Improved• Final Thoughtso Hidden Fieldso Using List Boxes for Number RatingChapter 14: Advanced Navigation: The Popup MenuSub – Topics:• The Popup Menu Example• Final ThoughtsPart 4: Beyond the BasicsChapter 15: Action Wizard and JavaScriptSub – Topics:• Working with Action Wizardo Reuse JavaScript from Chapter 8• Is It a Custom Action or a Custom Command?o Create and Manage Custom CommandsChapter 16: Multi-State Check BoxesSub - Topics:• The Problem of Multi-State Check Boxes• Bonus Star Rating Idea• Select All or Deselect All Check Boxes at OnceChapter 17: Importing an Image into a ButtonSub - Topics:• Creating the ButtonChapter 18: Multiple FormattingSub - Topics:• The Problem of Multiple Formatting• Option 1: Do It Yourselfo Price Scripto No Price Scripto Adding a Degree Symbol and Formatting range• Option 2: Call a ProfessionalChapter 19: Digital Signatures and BarcodesSub - Topics:• Digital Signatures and Security• BarcodesChapter 20: What are E-Signature Forms and Web Forms?Sub - Topics:• A brief Look at E- Signatures and Resources• What are Web Forms, do they have JavaScript? and related ResourcesPart 5: Putting It into PracticeChapter 21: Homework AssignmentsSub - Topics:• Homework Assignment 1: Show and Hide• Homework Assignment 2: Working with JavaScript to Create Formulaso Area of a Circle (A = π r 2 )o Field: CircumferenceRow1 Circumference of a Circle (C = 2 π r )o Field: VolumeRow1 Volume of a Sphere (V = 4/3 π r3 )o Field: FahrenheitRow1 Celsius to Fahrenheit to Formula. (°C x 9/5) + 32 = °F.o Field: CelsiusRow1_2 Fahrenheit to Celsius Formula. (°F - 32) x 5/9 = °C• Homework Assignment 3: Custom Validation and Regular Expressions• Homework Assignment 4: Personal Dropdown Menu and Definitions Text Box
Introduction to Prescriptive AI
Gain a working knowledge of prescriptive AI, its history, and its current and future trends. This book will help you evaluate different AI-driven predictive analytics techniques and help you incorporate decision intelligence into your business workflow through real-world examples.The book kicks off with an introduction to decision intelligence and provides insight into prescriptive AI and how it can be woven into various business strategies and frameworks. You'll then be introduced to different decision intelligence methodologies and how to implement them, along with advantages and limitations of each. Digging deeper, the authors then walk you through how to perform simulations and interpret the results. A full chapter is devoted to embedding decision intelligence processes and outcomes into your business workflow using various applications. The book concludes by exploring different cognitive biases humans are prone to, and how those biases can be eliminated by combining machine and human intelligence.Upon completing this book, you will understand prescriptive AI, tools, and techniques and will be ready to incorporate them into your business workflow.WHAT YOU WILL LEARN* Implement full-fledged decision intelligence applications using Python* Leverage the tools, techniques, and methodologies for prescriptive AI* Understand how prescriptive AI can be used in different domains through practical examples* Interpret results and integrate them into your decision makingWHO THIS BOOK IS FORData Scientists and Machine Learning Engineers, as well as business professionals who want to understand how AI-driven decision intelligence can help grow their business.AKSHAY R. KULKARNI is an artificial intelligence (AI) and machine learning (ML) evangelist and a thought leader. He has consulted several Fortune 500 and global enterprises to drive AI and data science–led strategic transformations. He is a Google developer, an author, and a regular speaker at major AI and data science conferences (including the O’Reilly Strata Data & AI Conference and Great International Developer Summit (GIDS)) . He is a visiting faculty member at some of the top graduate institutes in India. In 2019, he was featured as one of India’s “top 40 under 40” data scientists. In his spare time, Akshay enjoys reading, writing, coding, and helping aspiring data scientists. He lives in Bangalore with his family.ADARSHA SHIVANANDA is a data science and MLOps leader. He is working on creating world-class MLOps capabilities to ensure continuous value delivery from AI. He aims to build a pool of exceptional data scientists within and outside organizations to solve problems through training programs. He always wants to stay ahead of the curve. Adarsha has worked extensively in the pharma, healthcare, CPG, retail, and marketing domains. He lives in Bangalore and loves to read and teach data science.AVINASH MANURE is a seasoned Machine Learning Professional with 10+ years of experience building, deploying, and maintaining state-of-the-art machine learning solutions across different industries. He has 6+ years of experience leading and mentoring high-performance teams in developing ML systems catering to different business requirements. He is proficient in deploying complex machine learning and statistical modeling algorithms/techniques for identifying patterns and extracting valuable insights for key stakeholders and organizational leadership.Chapter 1: Decision Intelligence Overview.- Chapter 2: Decision Intelligence Requirements.- Chapter 3: Decision Intelligence Methodologies.- Chapter 4: Interpreting Results from Different Methodologies.- Chapter 5: Augmenting Decision Intelligence Results into the Business Workflow.- Chapter 6: Actions, Biases and Human-in-the-Loop.- Chapter 7: Case Studies.
Angewandte Data Science
Die Anwendungen der Disziplin Data Science erweitern und wandeln sich stetig. In diesem Buch geben Insider aus Praxis, Wissenschaft und Lehre detailliert die Ergebnisse ihrer Data-Science-Projekte, Methodenwissen sowie Knowhow zu Vorgehensweisen und Prozessmodellen an den Leser weiter. Dabei wird ein weit gespannter Querschnitt an konkreten Anwendungen beschrieben, erklärt und illustriert: von der Nutzung generativer KI-Systeme über quantitative Textanalyse, Predictive Policing, Erklärbarkeit von Machine-Learning-Modellen, experimentelle Datenanalyse in der Spektroskopie bis hin zu Datenvisualisierung, Strukturgleichungsmodellen und Varianzanalyse.Das Buch richtet sich an jeden, der sowohl am konkreten Einsatz von Datenwissenschaft, Statistik, Maschinellem Lernen und Künstlicher Intelligenz als auch am zugehörigen theoretischen Hintergrund interessiert ist. Praktikern, Studierenden und Lehrenden dürfte es von besonderem Nutzen sein: eine Vielzahl an Abbildungen, Diagrammen und Illustrationen ergänzen die reichhaltigen Textinformationen; Links zu Webseiten und Webapplikationen verweisen auf online verfügbare weitere Informationsquellen und Data-Science-Werkzeuge.LOTHAR B. BLUM lehrt als Hochschuldozent interaktives Informationsdesign, Datenvisualisierung und Advanced Analytics. Er ist Principal UX Designer beim Cloudsoftwareunternehmen Infor sowie Co-Founder und Organisator der Data Science Darmstadt Meetups.Einflüsse der Corona-Pandemie auf die deutsche Presse-Sprache.- Predictive Policing.- Am Anfang war der Prompt.- Erklärbarkeit als Schlüssel für den verantwortungsvollen Umgang mit KI. - Strukturgleichungsmodelle versus Varianzanalyse.- Was ist schon normal in diesen Zeiten? - Sankey-Diagramm reloaded.- Jenseits der Algorithmen.- A Scalable Architecture for Smart Genomic Data Analysis in Medical Laboratories.- Die Sieben V der Daten.– Scope Creep, GUI, Skalierung.
Pro Cryptography and Cryptanalysis with C++23
Develop strong skills for writing cryptographic algorithms and security schemes/modules using C++23 and its new features. This book will teach you the right methods for writing advanced cryptographic algorithms, such as elliptic curve cryptography algorithms, lattice-based cryptography, searchable encryption, and homomorphic encryption. You'll also examine internal cryptographic mechanisms and discover common ways in which the algorithms can be implemented and used correctly in practice.The authors explain the mathematical basis of cryptographic algorithms in terms that a programmer can easily understand. They also show how “bad” cryptography can creep in during implementation and what “good” cryptography should look like by comparing advantages and disadvantages based on processing time, execution time, and reliability.WHAT YOU WILL LEARN* Discover what modern cryptographic algorithms and methods are used for * Design and implement advanced cryptographic mechanisms * See how C++23 and its new features are impact the implementation of cryptographic algorithms* Practice the basics of public key cryptography, including ECDSA signatures and more* See how most of the algorithms can be brokenWHO THIS BOOK IS FORProfessional programmers, developers, and software engineers who are developing cryptography algorithms and security schemes/modules in C++. Prior C++ programming and IDE experience and some basic experience of cryptography concepts (symmetric and asymmetric) highly recommended.MARIUS IULIAN MIHAILESCU, PHD is CEO at Dapyx Solution Ltd., a company based in Bucharest, Romania and involved in information security- and cryptography-related research projects. He is a lead guest editor for applied cryptography journals and a reviewer for multiple publications with information security and cryptography profiles. He authored and co-authored more than 30 articles in conference proceedings, 25 articles in journals, and three books. For more than six years he has served as a lecturer at well-known national and international universities (University of Bucharest, “Titu Maiorescu” University, Kadir Has University in, Istanbul, Turkey). He has taught courses on programming languages (C#, Java, C++, Haskell), and object-oriented system analysis and design with UML, graphs, databases, cryptography and information security. He served for three years as IT officer at Royal Caribbean Cruises Ltd. where he dealt with IT infrastructure, data security, and satellite communications systems. He received his PhD in 2014 and his thesis was on applied cryptography over biometrics data. He holds two MSc in information security and software engineering.STEFANIA LOREDANA NITA, PHD is a software developer at the Institute of Computer Science of the Romanian Academy and a PhD with her thesis on advanced cryptographic schemes using searchable encryption and homomorphic encryption. She has served more than two years as an assistant lecturer at the University of Bucharest where she taught courses on subjects such as advanced programming techniques, simulation methods, and operating systems. She has authored and co-authored more than 15 workpapers at conferences and journals, and has authored two books on he Haskell programming language. She is a lead guest editor for special issues on information security and cryptography such as Advanced Cryptography and Its Future: Searchable and Homomorphic Encryption. She holds an MSc in software engineering and two BSc in computer science and mathematics.Part I: Foundations1: Introduction2: Cryptography Fundamentals3: Mathematical Background and Its Applicability4: Large Integer Arithmetic5: Floating Point Arithmetic6: New Features in C++237: Secure Coding Guidelines8: Cryptography Libraries in C/C++23Part II: Pro Cryptography9: Elliptic Curve Cryptography10: Lattice-based Cryptography11: earchable Encryption12: Homomorphic Encryption13: (Ring) Learning with Errors Cryptography14: Chaos-based Cryptography15: Big Data Cryptography16:Cloud Computing CryptographyPart III: Pro Cryptanalysis17: Getting Started with Cryptanalysis18: Cryptanalysis Attacks and Techniques19: Linear and Differential Cryptanalysis20: Integral Cryptanalysis21: Brute Force and Buffer Overflow Attacks22: Text Characterization23: Implementation and Practical Approach of Cryptanalysis Methods
How to Catch a Phish
Learn how to detect, analyze, and respond to phishing emails, the top infection vector used by cybercriminals. The repeatable process described in this book has been cultivated and tested in real-life incidents and validated across multiple threat landscapes and environments.Every organization and individual with an email account is susceptible to deceptive emails sent by attackers with nefarious intentions. This activity, known as phishing, involves an attacker attempting to lure individuals into providing sensitive information or performing a predetermined action. Attacks vary in sophistication, but the core skills and process to detect, analyze, and respond to a suspicious message does not change.Attackers have preyed on victims with convincing and not-so-convincing phishing emails to gain initial footholds into networks around the world for over 30 years. This attack method has been rapidly growing in popularity and continues to be the number one method that organizations and individuals struggle to defend against. Regardless of what any vendor or organization will tell you, no infallible tool exists to eliminate this threat completely.This book teaches you how to analyze suspicious messages using free tools and resources. You will understand the basics of email, tactics used by attackers, and a repeatable process to systematically analyze messages and respond to suspicious activity.YOU WILL LEARN HOW TO:* Safely save email messages as attachments for analysis* Identify what information is in an email header* Review header information and extract key indicators or patterns used for detection* Identify signs of a suspicious or malicious email message* Detect the tactics that attackers use in phishing emails* Safely examine email links and attachments* Use a variety of free and simple tools to analyze email messagesWHO THIS BOOK IS FORCybersecurity professionals and interested computer security enthusiasts currently holding or aspiring to obtain positions such as IT Security Analyst, Network Defender, Security Operations Center Analyst, or Help Desk Technician. Readers should have a general understanding of how email works and some ways that attackers use this platform for initial access.Nick Oles is a cybersecurity expert with over 15 years of operational experience in military, industry, and academic environments. He has worked on incident response and threat hunting teams and consulted with Fortune 150 organizations, small businesses, and US Department of Defense entities. Nick has served his country for over a decade in the cyber and special operations communities, earning multiple military accolades, completing worldwide deployments, and serving in joint special operations environments. He has advised award-winning academic centers on cyber-program development and management, as well as created and taught academic and certification courses on a variety of cybersecurity topics. Nick has detected, analyzed, and responded to thousands of security incidents over his career. He continues to actively contribute to the cybersecurity community and teach students at all skill levels while still serving his country.CHAPTER 1. HOW EMAIL WORKS1.1 Understanding Email Architecture1.2 Basic Components of an email message1.2.1 Email Header1.2.2 Email ContentCHAPTER 2. PHISHING TACTICS AND TECHNIQUES2.1 How phishers get you to click2.1.1 Elicitation and enticement2.1.2 Key indicators of suspicious messagesCHAPTER 3. PICERL PROCESS EXPLAINED3.1 Preparation3.2 Identification3.3 Containment3.4 Eradication3.5 Remediation3.6 Lessons LearnedCHAPTER 4. ANALYZING MESSAGE CONTENTCHAPTER 5. EMBEDDED LINK ANALYSIS5.1 Process safely extract and find links5.2 Tools to submit links for analysisCHAPTER 6. ATTACHMENT ANALYSIS6.1 How to handle attachments6.2 Tools used to analyze attachmentsCHAPTER 7. LOG SEARCHING AND RESPONSE7.1 Key logs records to search7.2 Response verbiage and communicationCHAPTER 8. MITIGATION AND LESSONS LEARNED
The Active Defender
IMMERSE YOURSELF IN THE OFFENSIVE SECURITY MINDSET TO BETTER DEFEND AGAINST ATTACKSIn The Active Defender: Immersion in the Offensive Security Mindset, Senior Information Security Forensic Analyst Dr. Catherine J. Ullman delivers an expert treatment of the Active Defender approach to information security. In the book, you’ll learn to understand and embrace the knowledge you can gain from the offensive security community. You’ll become familiar with the hacker mindset, which allows you to gain emergent insight into how attackers operate and better grasp the nature of the risks and threats in your environment. The author immerses you in the hacker mindset and the offensive security culture to better prepare you to defend against threats of all kinds. You’ll also find:* Explanations of what an Active Defender is and how that differs from traditional defense models* Reasons why thinking like a hacker makes you a better defender* Ways to begin your journey as an Active Defender and leverage the hacker mindsetAn insightful and original book representing a new and effective approach to cybersecurity, The Active Defender will be of significant benefit to information security professionals, system administrators, network administrators, and other tech professionals with an interest or stake in their organization’s information security. CATHERINE J. ULLMAN is a security researcher, speaker, and Principal Technology Architect, Security at the University at Buffalo. She is a DFIR specialist and expert in incident management, intrusion detection, investigative services, and personnel case resolution. She offers security awareness training in an academic setting and is a well-known presenter at information security conferences, including DEF CON and Blue Team Con.
Künstliche Intelligenz und Data Science in Theorie und Praxis
Dieser Sammelband verbindet theoretische Grundlagen und praktische Anwendungen von Künstlicher Intelligenz (KI) und Data Science: Anerkannte Experten stellen in ihren Beiträgen den aktuellen Stand in Forschung und Wirtschaft dar – und bieten so einen einzigartigen Überblick über aktuelle Konzepte und ihre Umsetzung in Unternehmen.Im ersten Teil des Buchs werden die Methoden und Algorithmen skizziert, die sich größtenteils aus einer Kombination von Statistik und Informatik ergeben und auf Verfahren des Maschinellen Lernens bis hin zu Deep Learning und KI basieren. Im zweiten Teil wird die konzeptionelle Umsetzung in der Praxis skizziert: Hier wird insbesondere aufgezeigt, welche Herausforderungen in der Praxis auftreten – ob nun bei der Einbettung der Daten-Use-Cases in eine Gesamtstrategie oder bei der Produktivsetzung, Weiterentwicklung und dem Betrieb von Daten-basierten Lösungen. Der dritte Teil zeigt das breite Potpourri von Data Science in der Praxis: Branchengrößenwie Allianz, ADAC, BMW, Deutsche Bahn, Lufthansa, REWE, RTL, St. Galler Stadtwerke, SwissRe und viele weitere zeigen konkret, welche Erfahrungen sie bei ihren Projekten gesammelt haben. Fachartikel von über 20 namhaften Unternehmen decken die spezifischen Anforderungen ihrer jeweiligen Branchen ab.Das Buch möchte die interdisziplinäre Diskussion und Kooperation zwischen Wissenschaft und Wirtschaft fördern und richtet sich daher an verschiedene Lesergruppen:* Studierende und Absolventen, die Orientierung für die eigene Laufbahn suchen.* Forschende und Lehrende, die einen Einblick in praxisrelevante Einsatzgebiete erhalten möchten.* Anwender, Praktiker und Entscheider, die sich über Chancen und Herausforderungen von KI in der Praxis informieren möchten.ANDREAS GILLHUBER ist Co-CEO bei der Alexander Thamm GmbH, einer führenden Beratung für Data Science, KI und ML im deutschsprachigen Raum.GÖRAN KAUERMANN ist Universitätsprofessor an der Ludwigs-Maximilians-Universität München und hat dort den Elite-Studiengang Data Science eingerichtet.WOLFGANG HAUNER ist als Leiter Group Data Analytics der Allianz SE global verantwortlich für Daten- und Analytics-Lösungen für die Allianz Unternehmensgruppe.Vorwort.- Grundlagen von Data Science.- Data Science in der Praxis.- Beispiele aus der Praxis-Ausblick/Wohin geht die Reise.
Data Wrangling
DATA WRANGLINGWRITTEN AND EDITED BY SOME OF THE WORLD’S TOP EXPERTS IN THE FIELD, THIS EXCITING NEW VOLUME PROVIDES STATE-OF-THE-ART RESEARCH AND LATEST TECHNOLOGICAL BREAKTHROUGHS IN DATA WRANGLING, ITS THEORETICAL CONCEPTS, PRACTICAL APPLICATIONS, AND TOOLS FOR SOLVING EVERYDAY PROBLEMS.Data wrangling is the process of cleaning and unifying messy and complex data sets for easy access and analysis. This process typically includes manually converting and mapping data from one raw form into another format to allow for more convenient consumption and organization of the data. Data wrangling is increasingly ubiquitous at today’s top firms. Data cleaning focuses on removing inaccurate data from your data set whereas data wrangling focuses on transforming the data’s format, typically by converting “raw” data into another format more suitable for use. Data wrangling is a necessary component of any business. Data wrangling solutions are specifically designed and architected to handle diverse, complex data at any scale, including many applications, such as Datameer, Infogix, Paxata, Talend, Tamr, TMMData, and Trifacta. This book synthesizes the processes of data wrangling into a comprehensive overview, with a strong focus on recent and rapidly evolving agile analytic processes in data-driven enterprises, for businesses and other enterprises to use to find solutions for their everyday problems and practical applications. Whether for the veteran engineer, scientist, or other industry professional, this book is a must have for any library. M. NIRANJANAMURTHY, PhD, is an assistant professor in the Department of Computer Applications, M S Ramaiah Institute of Technology, Bangalore, Karnataka. He earned his PhD in computer science at JJTU, Rajasthan, India. He has over 11 years of teaching experience and two years of industry experience as a software engineer. He has published several books, and he is working on numerous books for Scrivener Publishing. He has published over 60 papers for scholarly journals and conferences, and he is working as a reviewer in 22 scientific journals. He also has numerous awards to his credit. Kavita Sheoran, PhD, is an associate professor in the Computer Science Department, MSIT, Delhi, and she earned her PhD in computer science from Gautam Buddha University, Greater Noida. With over 17 years of teaching experience, she has published various papers in reputed journals and has published two books. GEETIKA DHAND, PhD, is an associate professor in the Department of Computer Science and Engineering at Maharaja Surajmal Institute of Technology. After earning her PhD in computer science from Manav Rachna International Institute of Research and Studies, Faridabad, she has taught for over 17 years. She has published one book and a number of papers in technical journals. PRABHJOT KAUR has over 19 years of teaching experience and has earned two PhDs for her work in two different research areas. She has authored two books and more than 40 research papers in reputed journals and conferences. She also has one patent to her credit.
Predicting the Unknown
As a society, we’re in a constant struggle to control uncertainty and predict the unknown. Quite often, we think of scientific fields and theories as being separate from each other. But a more careful investigation can uncover the common thread that ties many of those together. From ChatGPT, to Amazon’s Alexa, to Apple’s Siri, data science, and computer science have become part of our lives. In the meantime, the demand for data scientists has grown, as the field has been increasingly called the “sexiest profession.”This book attempts to specifically cover this gap in literature between data science, machine learning and artificial intelligence (AI). How was uncertainty approached historically, and how has it evolved since? What schools of thought exist in philosophy, mathematics, and engineering, and what role did they play in the development of data science? It uses the history of data science as a stepping stone to explain what the future might hold.Predicting the Unknown provides the framework that will help you understand where AI is headed, and how to best prepare for the world that’s coming in the next few years, both as a society and within a business. It is not technical and avoids equations or technical explanations, yet is written for the intellectually curious reader, and the technical expert interested in the historical details that can help contextualize how we got here.WHAT YOU’LL LEARN* Explore the bigger picture of data science and see how to best anticipate future changes in that field* Understand machine learning, AI, and data science* Examine data science and AI through engaging historical and human-centric narratives WHO IS THIS BOOK FORBusiness leaders and technology enthusiasts who are trying to understand how to think about data science and AIDr. Stylianos (Stelios) Kampakis is a data scientist, data science educator and blockchain expert with more than 10 years of experience. He has worked with decision makers from companies of all sizes: from startups to organizations like the US Navy, Vodafone ad British Land. His work expands multiple sectors including fintech (fraud detection and valuation models), sports analytics, health-tech, general AI, medical statistics, predictive maintenance and others. He has worked with many different types of technologies, from statistical models, to deep learning to blockchain and he has two patents pending to his name. He has also helped many people follow a career in data science and technology.He is a member of the Royal Statistical Society, honorary research fellow at the UCL Centre for Blockchain Technologies, a data science advisor for London Business School, and CEO of The Tesseract Academy and tokenomics auditor at Hacken. As a well-known data-science educator, he has published two books, both of them getting 5 stars on Amazon. His personal website gets more than 10k visitors per month, and he is also a data science influencer on LinkedIn.PREFACEAuthor’s note to the curious readerPROLOGUECHAPTER ONE – WHERE ARE WE NOW? A BRIEF HISTORY OF UNCERTAINTYNot all uncertainty is created equalCHAPTER TWO - TRUTH, LOGIC AND THE PROBLEM OF INDUCTIONThe first black swanCHAPTER THREE - SWANS AND SPACE INVADERSOccam’s razor, space invaders and lizard peopleCHAPTER FOUR - PROBABILITY: TO BAYES, OR NOT TO BAYES?Frequentist or Bayesian?The formulation of Bayes’ theoremAfter LaplaceCHAPTER FIVE - WHAT’S MATHS GOT TO DO WITH IT? THE POWER OF PROBABILITY DISTRIBUTIONSOther Distribution ModelsIssues with this view of uncertaintyBounds and limitsCHAPTER SIX - ALTERNATIVE IDEAS: FUZZY LOGIC AND INFORMATION THEORYInformation Theory – Measuring UncertaintyCHAPTER SEVEN – STATISTICS: THE OLDEST KID ON THE BLOCKDescriptive vs Inferential StatisticsHypothesis Testing: Significant or Not?What the p?Statistical modelling: A useful abstractionCHAPTER EIGHT - MACHINE LEARNING: INSIDE THE BLACK BOXData Science and History of Machine LearningChoose Your Learning Type: Supervised, Unsupervised, Reinforcement, or Other?The Bias-Variance Trade-OffMachine Learning vs Statistics: Why the ‘Dumb’ Approach WorksMachine Learning ShortcomingsCHAPTER NINE - CAUSALITY: UNDERSTANDING THE ‘WHY’How to Approach Causality?Causality in our MindCHAPTER TEN - FORECASTING, AND PREDICTING THE FUTURE: THE FOX AND THE TRUMPA brief history of forecastingForecasting in practice: Newton and the madness of men, Trump, Brexit, and losing money through mathematical modellingHow to do forecasting: A story of foxes and hedgehogsCHAPTER ELEVEN - THE LIMITS OF PREDICTION (PART A): A FUTILE PURSUIT?Learning theory: what can we know about what we don’t know?Monte Carlo Simulations: What Does a Casino Have to do with Science?CHAPTER TWELVE - THE LIMITS OF PREDICTION (PART B): GAME THEORY, AGENT-BASED MODELLING AND COMPLEXITY (ACTIONS AND REACTIONS)Agent-based Modelling: Crafting artificial WorldsComplexity Theory: Simulation vs the Limits of PredictionStudying Complexity is a Complex EndeavourLearning from Complexity: The Limits of Computation are the Limits of UncertaintyCHAPTER THIRTEEN - UNCERTAINTY IN US: HOW THE HUMAN MIND HANDLES UNCERTAINTYUncertainty and our MindUncertainty and our BrainCHAPTER FOURTEEN - BLOCKCHAIN: UNCERTAINTY IN TRANSACTIONSThe Internet of TrustHow Blockchain WorksFrom Crypto-Anarchism to Drug Trafficking: The unconventional Beginnings of an interesting TechnologyI Can’t Trust you, but I Can Trust the BlockchainCHAPTER FIFTEEN - ECONOMIES OF PREDICTION: A NEW INDUSTRIAL REVOLUTIONUncertainty brokersIndustries of incomplete InformationPrediction Industries and AutomationThe global Economy against UncertaintyEPILOGUE: THE CERTAINTY OF UNCERTAINTY
Understand, Manage, and Measure Cyber Risk
When it comes to managing cybersecurity in an organization, most organizations tussle with basic foundational components. This practitioner’s guide lays down those foundational components, with real client examples and pitfalls to avoid.A plethora of cybersecurity management resources are available—many with sound advice, management approaches, and technical solutions—but few with one common theme that pulls together management and technology, with a focus on executive oversight. Author Ryan Leirvik helps solve these common problems by providing a clear, easy-to-understand, and easy-to-deploy "playbook" for a cyber risk management approach applicable to your entire organization.This second edition provides tools and methods in a straight-forward, practical manner to guide the management of a cybersecurity program. Expanded sections include the critical integration of cyber risk management into enterprise risk management, the important connection between a Software Bill of Materials and Third-party Risk Programs, and additional "how to" tools and material for mapping frameworks to controls.PRAISE FOR UNDERSTAND, MANAGE, AND MEASURE CYBER RISKWhat lies ahead of you in the pages of this book? Clean practicality, not something that just looks good on paper—brittle and impractical when exposed to the real world. I prize flexibility and simplicity instead of attempting to have answers for everything and the rigidity that results. This simplicity is what I find valuable within Ryan's book. TIM COLLYER, MOTOROLA SOLUTIONSIt seems that I have found a kindred spirit—a builder who has worked with a wide variety of client CISOs on their programs, gaining a deep understanding of how a successful and sustainable program should be constructed. Ryan's cyber work in the US Department of Defense, his McKinsey & Company consulting, and his advisory and survey work with IANS give him a unique global view of our shared passion. NICHOLAS J. MANKOVICH, PHD, MS, CISPPWHO THIS BOOK IS FORCISOs, CROs, CIOs, directors of risk management, and anyone struggling to pull together frameworks or basic metrics to quantify uncertainty and address riskRYAN LEIRVIK is a cybersecurity professional who has spent the better part of two decades enhancing information security programs at the world's largest institutions. With considerable US government and commercial sector experience, Ryan has employed his professional passion for cybersecurity at almost every level within an organization.A frequent speaker on the topic of information security, Ryan fields several questions on “How do I make sure I have a sustainable cyber program?” This book was written to help answer that question.Ryan has been the CEO of a cybersecurity research and development company, Chief of Staff and Associate Director of Cyber for the US Department of Defense, and a cybersecurity strategy consultant with McKinsey & Company. Ryan’s technology career started at IBM, and he has a master of IT degree from Virginia Tech, an MBA from Case Western Reserve University, as well as a bachelor of science from Purdue University. Ryan is also on the faculty at IANS.INTRODUCTIONPART 1: THE PROBLEMCHAPTER 1: THE SITUATIONCHAPTER 2: THE COMPLICATIONInformation Technology or “IT” became pervasive near 1995, and after a quarter-century of IT in organizations, managers, engineers, and board-level oversight still speak different languages. The language divide creates a disconnect in the strategy-to-management-to-tactical thread that is critical for overall organizational risk management, not to mention overall business management. This complicates the ability for these functions to align on one language for managing cyber risk.CHAPTER 3: THE RESOLUTIONOne unified approach to cybersecurity:· Be clear on identifying the risk· Understand the risk· Categorize the critical data at risk· Determine the causes, consequences, and accountability of a data breach· Identify the business impact of a breach· Simplify how you manage the risk· Apply a framework· Structure the organization (i.e., staff and management)· Prepare to respond (... and recover)· Build feedback mechanisms to measure the risk· Choose risk-informative metrics, Key Performance Indicators (KPI’s), and Key Risk Indicators (KPI’s· Apply appropriate resources (e.g., measuring projects, overseeing initiatives)PART 2: THE SOLUTIONCHAPTER 4: UNDERSTAND THE PROBLEMKnowing what “problem” you are solving is the most critical part of problem solving. It is important to spend time exploring the main issue. This typically means asking others what they see as the problem, gathering facts and opinions (and knowing the difference between them), and then establishing a recommended problem to solve that categorically encompasses all the facts you have gathered. For example, the audit team will likely talk about the problem of fines and resources to remain in compliance. The contracts team will likely talk about the risks brought about by outside companies (aka Third Parties), and the tech teams will likely talk about the immediate risks to the network, applications, or endpoints. Each team is looking at their part of the enterprise risk, but are they all looking to one specific problem that aligns them all? Typically not. So, the solution becomes the one problem everyone is solving for and helps them focus on that. In this case, that might be: critical data and systems at risk. Communicating as one problem everyone is solving for has the benefit of pulling everyone together, instead of trying to manage everyone from within their view of the problem -- risk to critical data or systems. The solution here is to get them all focused on one problem so that managing the problem is much easier -- with everyone understanding that the problem is (i.e., keeping critical data and systems secure), the management of that becomes an easier tactical activity.CHAPTER 5: MANAGE THE PROBLEM· Guidelines up front: Settle on one approach (i.e., Framework) that best fits the business· Complication is that no one framework fits any one organization’s risk profile perfectly· Key is to pick a framework as a starting point and modify it to the organization (and as cyber risk management matures)· Key to resolving this is to assign roles (e.g., an adversary, a manager, a third party); remember, there is a person at the center of the problem you are trying to manageCHAPTER 6: MEASURE THE PROBLEM· Guidelines up front: Board-level metrics are strategic, supported by tactical measures.· Objective is to communicate three things: (1) Understand what is at risk; (2) Manage that risk; and (3) Measure your management through feedback metrics· Educate the Board on what you are doing to reduce the risk· Communicate the value of your programs: provide insightful measures· Mature measures: measure what you can measure now, with a focus on what you want to measureCHAPTER 7: CONCLUSION* BE CLEAR ON IDENTIFYING THE RISK· Understand the risk· Categorize the critical data at risk· Determine the causes, consequences, and accountability of a data breach· Identify the business impact of a breach* SIMPLIFY HOW YOU MANAGE THE RISK · Apply a framework· Structure the organization (i.e., staff and management)· Prepare to respond (... and recover)* BUILD FEEDBACK MECHANISMS TO MEASURE THE RISK· Choose risk-informative metrics, Key Performance Indicators (KPI’s), and Key Risk Indicators (KPI’s· Apply appropriate resources (e.g., measuring projects, overseeing initiatives)APPENDIX: COMMON QUESTIONS (TBD)APPENDIX: ILLUSTRATIONS (TBD)
Beginning Microsoft Dataverse
Understand the role that Dataverse plays in the low-code revolution that helps businesses gain advantage from being more agile with technology. This book shows you how to use Dataverse to solve business problems by describing the layers of a solution in the Power Platform and the options that exist at each layer so you can make informed decisions as you develop your solutions. The book shows how Dataverse is a central piece of the Microsoft Power Platform and helps tech-savvy professionals move nimbly and seize the day when opportunities present themselves.The book starts out by covering the platform in terms of its layers so you can orient yourself with the features that exist at each level and what that means to you as a developer. You will learn how to work inside the data layer to design tables to store data and relationships and manage how it all works together. You will learn how to apply business logic and validation in the business layer to ensure data integrity and enforce process compliance. You will learn how to design interfaces in the presentation layer to allow users to interact with your data and processes in user-friendly applications. And you will learn how to utilize third-party integration tools to create seamless connections between your solution and legacy systems so you can develop enterprise-grade tools in record time.WHAT YOU WILL LEARN* Understand the layers of Dataverse and the features at each layer* Create tables and relationships to store data and manage interactions* Build applications to allow users to interact with your data using logical interfaces* Design business logic and workflows to ensure data integrity and automation* Configure security to control access to data and prevent unauthorized access* Explore the options for integration with third-party systems WHO THIS BOOK IS FORMicrosoft Power Platform users who want to learn how to access the power of the Power Platform and leverage Dataverse to build powerful, robust, and resilient tools; power users and citizen developers who are looking for tools to quickly build scalable business solutions that don’t require a strong developer background; pro developers who want to learn how to utilize use the Power Platform to speed up the development cycle and deliver value to customers faster than ever beforeBRIAN HODEL is a Microsoft Power Platform developer who is passionate about solving problems. His background in Lean Six Sigma and interest in application development converged as he began using what would eventually come to be known as the Power Platform. Since then, he has been developing enterprise solutions based on Dataverse in the Power Platform, speaking at conferences, participating on Customer Advisory Boards with Microsoft product development teams, and leading the internal Power Champions group at his current company. 1. Microsoft Power Platform2. Planning Your Solution Design3. Data Layer4. Business Logic Layer5. Presentation Layer6. Security7. Integration with Third-Party Tools8. Dataverse for Teams
Software im Automobil
Dieses Fach- und Lehrbuch enthält die maschinengenerierten Zusammenfassungen einer Datenbankrecherche zum Thema „Software im Automobil“. Die Vorgabe der Stichworte, die Struktur und die Selektion der Inhalte wurde vom Autor vorgenommen. Darüber hinaus hat der Autor die enthaltenen Artikel durch Einleitungen und Bewertungen in einen übergreifenden Zusammenhang gebracht und kommentiert. Auf diese Weise ist ein Werk entstanden, das Studierenden sowie Berufseinsteigern einen breiten Überblick über das fachliche Feld sowie Hinweise zur weiterführenden Literatur gibt und auf die weitere Arbeit in diesem Bereich vorbereitet. Fahrzeugarchitektur und Infrastruktur.- Software-basierte Funktionen.- Strukturierte Softwareentwicklung.- Software-Tests.- Reifegrad der Softwareentwicklung.
Functional Programming in R 4
Master functions and discover how to write functional programs in R. In this book, updated for R 4, you'll learn to make your functions pure by avoiding side effects, write functions that manipulate other functions, and construct complex functions using simpler functions as building blocks.In Functional Programming in R 4, you’ll see how to replace loops, which can have side-effects, with recursive functions that can more easily avoid them. In addition, the book covers why you shouldn't use recursion when loops are more efficient and how you can get the best of both worlds.Functional programming is a style of programming, like object-oriented programming, but one that focuses on data transformations and calculations rather than objects and state. Where in object-oriented programming you model your programs by describing which states an object can be in and how methods will reveal or modify that state, in functional programming you model programs by describing how functions translate input data to output data. Functions themselves are considered to be data you can manipulate and much of the strength of functional programming comes from manipulating functions; that is, building more complex functions by combining simpler functions.WHAT YOU'LL LEARN* Write functions in R 4, including infix operators and replacement functions* Create higher order functions* Pass functions to other functions and start using functions as data you can manipulate* Use Filer, Map and Reduce functions to express the intent behind code clearly and safely* Build new functions from existing functions without necessarily writing any new functions, using point-free programming* Create functions that carry data along with themWHO THIS BOOK IS FORThose with at least some experience with programming in R.THOMAS MAILUND is Senior Software Architect at Kvantify, a quantum computing company from Denmark. He has a background in math and computer science. He now works on developing algorithms for computational problems applicable for quantum computing. He previously worked at the Bioinformatics Research Centre, Aarhus University, on genetics and evolutionary studies, particularly comparative genomics, speciation, and gene flow between emerging species. He has published Beginning Data Science in R with Apress, as well as other books out there.1. Functions in R2. Pure Functional Programming3. Scope and Closures4. Higher-order Functions5. Filer, Map, and Reduce6. Point-free Programming Afterword
Getting Started with SQL and Databases
Learn the basics of writing SQL scripts. Using Standard SQL as the starting point, this book teaches writing SQL in various popular dialects, including PostgreSQL, MySQL/MariaDB, Microsoft SQL Server, Oracle, and SQLite.The book starts with a general introduction to writing SQL and covers the basic concepts. Author Mark Simon then covers database principles, and how database tables are designed. He teaches you how to filter data using the WHERE clause, and you will work with NULL, numbers, dates, and strings. You will also understand sorting results using the ORDER BY clause, sorting by calculated columns, and limiting the number of results. By the end of the book, you will know how to insert and update data, and summarize data with aggregate functions and groups. Three appendices cover differences between SQL dialects, working with tables, and a crash course in PDO.WHAT YOU WILL LEARN* Filter, sort, and calculate data* Summarize data with aggregate functions* Modify data with insert, update, and delete statements* Study design principles in developing a databaseWHO THIS BOOK IS FORDevelopers and analysts working with SQL, as well as web developers who want a stronger understanding of working with databasesMARK SIMON has been involved in training and education since the beginning of his career. He started as a teacher of mathematics but soon moved into IT consultancy and training because computers are much easier to work with than high school students! He has worked with and trained in several programming and coding languages, and currently focuses on web development and database languages. When not involved in work, you will generally find Mark listening to or playing music, reading, or just wandering about.The appendix will include:* Notes on using SQL with PHP* “Cultural Notes” - a description of some of the sample data* Major Differences between DBMSs* Setting up the Sample Database