This book provides extensive insights on blockchain systems, starting from a historical perspective and moving towards building foundational knowledge, with focus on communication networks. It covers blockchain applications, algorithms, architectures, design and implementation, and security and privacy issues, providing the reader with a comprehensive overview. Further, it discusses blockchain systems and its integration to communication networks. The book includes hands-on, practical tutorials, self-assessment exercises, and review questions; tips and sample programs are also provided throughout. Complementary supporting material for instructors, including open source programming code for practical tutorials and exercises, is also available. The target audience includes graduate students, professionals, and researchers working in the areas of blockchain systems, distributed ledger technology, computer networks and communications, artificial intelligence, and cybersecurity.

This open access book provides the first comprehensive collection of papers that provide an integrative view on cybersecurity. It discusses theories, problems and solutions on the relevant ethical issues involved. This work is sorely needed in a world where cybersecurity has become indispensable to protect trust and confidence in the digital infrastructure whilst respecting fundamental values like equality, fairness, freedom, or privacy. The book has a strong practical focus as it includes case studies outlining ethical issues in cybersecurity and presenting guidelines and other measures to tackle those issues. It is thus not only relevant for academics but also for practitioners in cybersecurity such as providers of security software, governmental CERTs or Chief Security Officers in companies.

Understand the CCPA (California Consumer Privacy Act) and how to implement strategies to comply with this privacy regulation. Established in June 2018, the CCPA was created to remedy the lack of comprehensive privacy regulation in the state of California. When it comes into effect on January 1, 2020, the CCPA will give California residents the right to: Learn what personal data a business has collected about them Understand who this data has been disclosed to Find out whether their personal data has been sold to third parties, and who these third parties are Opt-out of such data transactions, or request that the data be deleted. Many organizations that do business in the state of California must align to the provisions of the CCPA. Much like the EU's GDPR (General Data Protection Regulation), businesses that fail to comply with the CCPA will face economic penalties. Prepare your business for CCPA compliance with our implementation guide that: Provides the reader with a comprehensive understanding of the legislation by explaining key terms Explains how a business can implement strategies to comply with the CCPA Discusses potential developments of the CCPA to further aid compliance Your guide to understanding the CCPA and how you can implement a strategy to comply with this legislation - buy this book today to get the guidance you need! About the author Preston Bukaty is an attorney and consultant. He specializes in data privacy GRC projects, from data inventory audits to gap analyses, contract management, and remediation planning. His compliance background and experience operationalizing compliance in a variety of industries give him a strong understanding of the legal issues presented by international regulatory frameworks. Having conducted more than 3,000 data mapping audits, he also understands the practical realities of project management in operationalizing compliance initiatives. Preston's legal experience and enthusiasm for technology make him uniquely suited to understanding the business impact of privacy regulations such as the GDPR and the CCPA. He has advised more than 250 organizations engaged in businesses as varied as SaaS platforms, mobile geolocation applications, GNSS/telematics tools, financial institutions, fleet management software, architectural/engineering design systems, and web hosting. He also teaches certification courses on GDPR compliance and ISO 27001 implementation, and writes on data privacy law topics. Preston lives in Denver, Colorado. Prior to working as a data privacy consultant, he worked for an international GPS software company, advising business areas on compliance issues across 140 countries. Preston holds a juris doctorate from the University of Kansas School of Law, along with a basketball signed by Hall of Fame coach Bill Self.

Focused on the latest mobile technologies, this book addresses specific features (such as IoT) and their adoptions that aim to enable excellence in business in Industry 4.0. Furthermore, this book explores how the adoption of these technologies is related to rising concerns about privacy and trusted communication issues that concern management and leaders of business organizations. Managing IoT and Mobile Technologies with Innovation, Trust, and Sustainable Computing not only targets IT experts and drills down on the technical issues but also provides readers from various groups with a well-linked concept about how the latest trends of mobile technologies are closely related to daily living and the workplace at managerial and even individual levels.

Features In-depth coverage of the role of AI in smart healthcare. Research guideline for AI and data science researchers/practitioners interested in the healthcare sector. Comprehensive coverage on security and privacy issues for AI in smart healthcare.

This book takes a holistic view of the roles of ICTs during the pandemic through the lens of social informatics, as it is critical to our understanding of the relations between society and technology. Specific attention is given to various stakeholders and social contexts, with analysis at the individual, group, community, and society levels. Pushing the boundaries of information science research with timely and critical research questions, this edited volume showcases information science research in the context of COVID-19, by specifically accentuating sociotechnical practices, activities, and ICT interventions during the pandemic. Its social informatics focus appeals to a broad audience, and its global and international orientation provides a timely, innovative, and much-needed perspective to information science. This book is unique in its interdisciplinary nature as it consists of research studies on the intersections between ICTs and health, culture, social interaction, civic engagement, information dissemination, work, and education. Chapters apply a range of research methods, including questionnaire surveys, content analyses, and case studies from countries in Asia, Europe, and America, as well as global and international comparisons. The book's primary target audience includes scholars and students in information and library science, particularly those interested in the social aspect of the information society. It may be of interest to information professionals, library practitioners, educators, and information policymakers, as well as scholars and students in science and technology studies, cultural studies, political science, public administration, sociology, and communication studies.

This book discusses artificial intelligence (AI) and cybersecurity from multiple points of view. The diverse chapters reveal modern trends and challenges related to the use of artificial intelligence when considering privacy, cyber-attacks and defense as well as applications from malware detection to radio signal intelligence. The chapters are contributed by an international team of renown researchers and professionals in the field of AI and cybersecurity. During the last few decades the rise of modern AI solutions that surpass humans in specific tasks has occurred. Moreover, these new technologies provide new methods of automating cybersecurity tasks. In addition to the privacy, ethics and cybersecurity concerns, the readers learn several new cutting edge applications of AI technologies. Researchers working in AI and cybersecurity as well as advanced level students studying computer science and electrical engineering with a focus on AI and Cybersecurity will find this book useful as a reference. Professionals working within these related fields will also want to purchase this book as a reference.

This book focuses on differential privacy and its application with an emphasis on technical and application aspects. This book also presents the most recent research on differential privacy with a theory perspective. It provides an approachable strategy for researchers and engineers to implement differential privacy in real world applications. Early chapters are focused on two major directions, differentially private data publishing and differentially private data analysis. Data publishing focuses on how to modify the original dataset or the queries with the guarantee of differential privacy. Privacy data analysis concentrates on how to modify the data analysis algorithm to satisfy differential privacy, while retaining a high mining accuracy. The authors also introduce several applications in real world applications, including recommender systems and location privacy Advanced level students in computer science and engineering, as well as researchers and professionals working in privacy preserving, data mining, machine learning and data analysis will find this book useful as a reference. Engineers in database, network security, social networks and web services will also find this book useful.

Software Security: Concepts & Practices is designed as a textbook and explores fundamental security theories that govern common software security technical issues. It focuses on the practical programming materials that will teach readers how to implement security solutions using the most popular software packages. It's not limited to any specific cybersecurity subtopics and the chapters touch upon a wide range of cybersecurity domains, ranging from malware to biometrics and more. Features The book presents the implementation of a unique socio-technical solution for real-time cybersecurity awareness. It provides comprehensible knowledge about security, risk, protection, estimation, knowledge and governance. Various emerging standards, models, metrics, continuous updates and tools are described to understand security principals and mitigation mechanism for higher security. The book also explores common vulnerabilities plaguing today's web applications. The book is aimed primarily at advanced undergraduates and graduates studying computer science, artificial intelligence and information technology. Researchers and professionals will also find this book useful.

A collection of best practices and effective implementation recommendations that are proven to work, Secure, Resilient, and Agile Software Development leaves the boring details of software security theory out of the discussion as much as possible to concentrate on practical applied software security for practical people. Written to aid your career as well as your organization, the book shows how to gain skills in secure and resilient software development and related tasks. The book explains how to integrate these development skills into your daily duties, thereby increasing your professional value to your company, your management, your community, and your industry. Secure, Resilient, and Agile Software Development was written for the following professionals: AppSec architects and program managers in information security organizations Enterprise architecture teams with application development focus Scrum teams DevOps teams Product owners and their managers Project managers Application security auditors With a detailed look at Agile and Scrum software development methodologies, this book explains how security controls need to change in light of an entirely new paradigm on how software is developed. It focuses on ways to educate everyone who has a hand in any software development project with appropriate and practical skills to Build Security In. After covering foundational and fundamental principles for secure application design, this book dives into concepts, techniques, and design goals to meet well-understood acceptance criteria on features an application must implement. It also explains how the design sprint is adapted for proper consideration of security as well as defensive programming techniques. The book concludes with a look at white box application analysis and sprint-based activities to improve the security and quality of software under development.

The Home in the Digital Age is a set of multidisciplinary studies exploring the impact of digital technologies in the home, with a shift of emphasis from technology to the people living and using this in their homes. The book covers a wide variety of topics on the design, introduction and use of digital technologies in the home, combining the technological dimension with the cognitive, emotional, cultural and symbolic dimensions of the objects that incorporate digital technologies and project them onto people's lives. It offers a coherent approach, that of the home, which gives unity to the discussion. Scholars of the home, the house and the family will find here the connection with the problems derived from the use of domestic robots and connected devices. Students of artificial intelligence, machine learning, robotics, big data and other branches of digital technologies will find ideas and arguments to apply their disciplines to the home and participate fruitfully in forums where digital technologies are built and negotiated in the home. Experts from various disciplines psychologists and sociologists; philosophers, epistemologists and ethicists; economists; engineers, architects, urban planners and designers and so on and also those interested in developing policies for the home and family will find this book contains well-founded and useful ideas to focus their work.

This open access book aims to set an agenda for research and action in the field of Digital Humanism through short essays written by selected thinkers from a variety of disciplines, including computer science, philosophy, education, law, economics, history, anthropology, political science, and sociology. This initiative emerged from the Vienna Manifesto on Digital Humanism and the associated lecture series. Digital Humanism deals with the complex relationships between people and machines in digital times. It acknowledges the potential of information technology. At the same time, it points to societal threats such as privacy violations and ethical concerns around artificial intelligence, automation and loss of jobs, ongoing monopolization on the Web, and sovereignty. Digital Humanism aims to address these topics with a sense of urgency but with a constructive mindset. The book argues for a Digital Humanism that analyses and, most importantly, influences the complex interplay of technology and humankind toward a better society and life while fully respecting universal human rights. It is a call to shaping technologies in accordance with human values and needs.

Updates content and introduces topics such as business changes and outsourcing. Addresses new cyber security risks such as IoT and Distributed Networks (i.e., blockchain). Covers strategy based on the OODA loop in the cycle. Demonstrates application of the concepts through short case studies of real-world incidents chronologically delineating related events. Discusses certifications and reference manuals in cyber security and digital forensics. Includes an entire chapter on tools used by professionals in the field.

Intelligent Cyber-Physical Systems Security for Industry 4.0: Applications, Challenges and Management presents new cyber-physical security findings for Industry 4.0 using emerging technologies like artificial intelligence (with machine/deep learning), data mining, applied mathematics. All these are the essential components for processing data, recognizing patterns, modeling new techniques, and improving the advantages of data science. Features * Presents an integrated approach with Cyber-Physical Systems, CPS security, and Industry 4.0 in one place * Exposes the necessity of security initiatives, standards, security policies, and procedures in the context of industry 4.0 * Suggests solutions for enhancing the protection of 5G and the Internet of Things (IoT) security * Promotes how optimization or intelligent techniques envisage the role of artificial intelligence-machine/deep learning (AI-ML/DL) in cyberphysical systems security for industry 4.0 This book is primarily aimed at graduates, researchers and professionals working in the field of security. Executives concerned with security management, knowledge dissemination, information, and policy development for data and network security in different educational, government, and non-government organizations will also find this book useful.

1) What to do when you get hacked 2) A guide to incident response 3) Incident response and cybersecurity for small businesses

Using both a theoretical argumentation and an empirical investigation, this book rationalizes the view that in order to understand people's privacy perceptions and behaviors, a situational perspective needs to be adopted. To this end, the book is divided into three parts. Part I advances the theory of situational privacy and self-disclosure by discussing impacts of new information and communication technologies on traditional theories of privacy and self-disclosure. Based on five basic suppositions, it describes three major processes of the theory: pre-situational privacy regulations processes, situational privacy perception and self-disclosure processes, and post-situational evaluation processes. Next, Part II presents the application of the theory to smartphone-based communication. It first analyses how people choose certain communication environments on their smartphones, how they manipulate them, and how these external factors affect self-disclosure within these environments. It then details a multi-method study conducted to test the derived assumptions and discusses the obtained results. Part III reflects on the overall implications of the theory, summarizes the major findings and lastly considers possible extensions and perspectives on future research. Intended mainly for researchers in privacy and communication studies, the book offers privacy scholars a systematic review of both classic and contemporary theories of privacy and self-disclosure. At the same time, communication scholars benefit from an additional methodological discussion of the mobile experience sampling method, which provides an invaluable approach to measuring situational communication processes.

As information processing continues to move toward an open systems environment, the advantages of authentication and key distribution systems over traditional passwords are becoming more and more evident. In this timely guide for computer scientists, electrical engineers, and networking specialists, author Rolf Oppliger explains and compares the various authentication and key distribution systems available today, including Kerberos, NetSP, SPX, TESS, and SESAME. The book explores the cryptographic techniques used for these systems - and shows how to use them to provide the best security for your network.

Privacy-Preserving Machine Learning is a practical guide to keeping ML data anonymous and secure. You'll learn the core principles behind different privacy preservation technologies, and how to put theory into practice for your own machine learning. Complex privacy-enhancing technologies are demystified through real world use cases forfacial recognition, cloud data storage, and more. Alongside skills for technical implementation, you'll learn about current and future machine learning privacy challenges and how to adapt technologies to your specific needs. By the time you're done, you'll be able to create machine learning systems that preserve user privacy without sacrificing data quality and model performance. Large-scale scandals such as the Facebook Cambridge Analytic a data breach have made many users wary of sharing sensitive and personal information. Demand has surged among machine learning engineers for privacy-preserving techniques that can keep users private details secure without adversely affecting the performance of models.

By the end of this book, the reader will understand: the difficulties of finding a needle in a haystack; creative solutions to address the problem; unique ways of engineering features and solving the problem of the lack of data (e.g. synthetic data). Additionally, the reader will be able to: avoid mistakes resulting from a lack of understanding; search for appropriate methods of feature engineering; locate the relevant technological solutions within the general context of decision-making.