Risk detection and cyber security play a vital role in the use and success of contemporary computing. By utilizing the latest technological advances, more effective prevention techniques can be developed to protect against cyber threats. Detecting and Mitigating Robotic Cyber Security Risks is an essential reference publication for the latest research on new methodologies and applications in the areas of robotic and digital security. Featuring extensive coverage on a broad range of topics, such as authentication techniques, cloud security, and mobile robotics, this book is ideally designed for students, researchers, scientists, and engineers seeking current research on methods, models, and implementations of optimized security in digital contexts.

Cyber security has become a topic of concern over the past decade as private industry, public administration, commerce, and communication have gained a greater online presence. As many individual and organizational activities continue to evolve in the digital sphere, new vulnerabilities arise. Cyber Security and Threats: Concepts, Methodologies, Tools, and Applications contains a compendium of the latest academic material on new methodologies and applications in the areas of digital security and threats. Including innovative studies on cloud security, online threat protection, and cryptography, this multi-volume book is an ideal source for IT specialists, administrators, researchers, and students interested in uncovering new ways to thwart cyber breaches and protect sensitive digital information.

The ubiquity and pervasive access to internet resources 24/7 by anyone from anywhere is enabling access to endless professional, educational, technical, business, industrial, medical, and government resources worldwide. To guarantee internet integrity and availability with confidentiality, the provision of proper and effective cyber security is critical for any organization across the world. AI Tools for Protecting and Preventing Sophisticated Cyber Attacks illuminates the most effective and practical applications of artificial intelligence (AI) in securing critical cyber infrastructure and internet communities worldwide. The book presents a collection of selected peer-reviewed chapters addressing the most important issues, technical solutions, and future research directions in cyber security. Covering topics such as assessment metrics, information security, and toolkits, this premier reference source is an essential resource for cyber security experts, cyber systems administrators, IT experts, internet and computer network professionals, organizational leaders, students and educators of higher education, researchers, and academicians.

In recent years, media digitalization has been booming. It has, however, led to a phenomenon of private data hacking, which was stimulated by the expansion of the data exchange system. These hackers are being countered by using new techniques, including cryptography and watermarking. Therefore, in the fields of information security, data encryption, and watermarking, there exists a need for a collection of original research in this area. Applications of Encryption and Watermarking for Information Security provides relevant theoretical frameworks and the latest empirical research findings in the domains of security and privacy. It is written for professionals who want to improve their understanding of the strategic role of trust at different levels of information security, that is, trust at the level of cryptography and watermarking and at the level of securing multimedia data. Covering topics such as background subtraction, moving object detection, and visual watermark identification, this premier reference source is an excellent resource for security and privacy professionals, IT managers, practitioners, students and educators of higher education, librarians, researchers, and academicians.

Multidisciplinary research is steadily revolutionizing traditional education, scientific approaches, and activities related to security matters. Therefore, the knowledge generated through multidisciplinary research into the field of application of scientific inquiry could be utilized to protect critical and vital assets of a country. The field of security requires focus on the assessment and resolution of complex systems. Consequently, the dynamics of the intelligence field leads to the necessity of raising awareness and placing priority on improved ideas using scientific inquiry. Intelligence and Law Enforcement in the 21st Century provides personnel directly working in the fields of intelligence and law enforcement with an opportunity to deeply delve into to the challenges, choices, and complications in finding, applying, and presenting the gathered intelligence through various methods and then presenting them through available policies and procedures in the arena of law and order. The book also addresses how law enforcement is critically assessed in the 21st century when implementing the rule of law and order. Covering topics such as counterterrorism, cybersecurity, biological and chemical weapons, and scientific inquiry, this is an essential text for law enforcement, intelligence specialists, analysts, cybersecurity professionals, government officials, students, teachers, professors, practitioners, and researchers in fields that include terrorism and national security.

With the rapid advancement in technology, myriad new threats have emerged in online environments. The broad spectrum of these digital risks requires new and innovative methods for protection against cybercrimes. The Handbook of Research on Network Forensics and Analysis Techniques is a current research publication that examines the advancements and growth of forensic research from a relatively obscure tradecraft to an important part of many investigations. Featuring coverage on a broad range of topics including cryptocurrency, hand-based biometrics, and cyberterrorism, this publication is geared toward professionals, computer forensics practitioners, engineers, researchers, and academics seeking relevant research on the development of forensic tools.

In today’s modern age of information, new technologies are quickly emerging and being deployed into the field of information technology. Cloud computing is a tool that has proven to be a versatile piece of software within IT. Unfortunately, the high usage of Cloud has raised many concerns related to privacy, security, and data protection that have prevented cloud computing solutions from becoming the prevalent alternative for mission critical systems. Up-to-date research and current techniques are needed to help solve these vulnerabilities in cloud computing. Modern Principles, Practices, and Algorithms for Cloud Security is a pivotal reference source that provides vital research on the application of privacy and security in cloud computing. While highlighting topics such as chaos theory, soft computing, and cloud forensics, this publication explores present techniques and methodologies, as well as current trends in cloud protection. This book is ideally designed for IT specialists, scientists, software developers, security analysts, computer engineers, academicians, researchers, and students seeking current research on the defense of cloud services.

The growth of innovative cyber threats, many based on metamorphosing techniques, has led to security breaches and the exposure of critical information in sites that were thought to be impenetrable. The consequences of these hacking actions were, inevitably, privacy violation, data corruption, or information leaking. Machine learning and data mining techniques have significant applications in the domains of privacy protection and cybersecurity, including intrusion detection, authentication, and website defacement detection, that can help to combat these breaches. Applications of Machine Learning and Deep Learning for Privacy and Cybersecurity provides machine and deep learning methods for analysis and characterization of events regarding privacy and anomaly detection as well as for establishing predictive models for cyber attacks or privacy violations. It provides case studies of the use of these techniques and discusses the expected future developments on privacy and cybersecurity applications. Covering topics such as behavior-based authentication, machine learning attacks, and privacy preservation, this book is a crucial resource for IT specialists, computer engineers, industry professionals, privacy specialists, security professionals, consultants, researchers, academicians, and students and educators of higher education.

This book focuses on major challenges posed by the Fourth Industrial Revolution (4IR), particularly the associated risks. By recognizing and addressing these risks, it bridges the gap between technological advancements and effective risk management. It further facilitates a swift adoption of technology and equips readers with the knowledge to be cautious during its implementation. Divided into three parts, it covers an overview of 4IR and explores the risks and risk management techniques and comprehensive risk management framework specifically tailored for the 4IR. Features: • Establishes a risk management framework for Industry 4.0 technologies. • Provides a ‘one stop shop’ of different technologies emerging in the Fourth Industrial Revolution. • Follows a consistent structure for each key Industry 4.0 technology in separate chapters. • Details required risk management skills for the technologies of the Fourth Industrial Revolution. • Covers risk monitoring, control, and mitigation measures. This book is aimed at graduate students, technology enthusiasts, and researchers in computer sciences, technology management, business management, and industrial engineering.

Machine learning has become one of the most prevalent topics in recent years. The application of machine learning we see today is a tip of the iceberg. The machine learning revolution has just started to roll out. It is becoming an integral part of all modern electronic devices. Applications in automation areas like automotive, security and surveillance, augmented reality, smart home, retail automation and healthcare are few of them. Robotics is also rising to dominate the automated world. The future applications of machine learning in the robotics area are still undiscovered to the common readers. We are, therefore, putting an effort to write this edited book on the future applications of machine learning on robotics where several applications have been included in separate chapters. The content of the book is technical. It has been tried to cover all possible application areas of Robotics using machine learning. This book will provide the future vision on the unexplored areas of applications of Robotics using machine learning. The ideas to be presented in this book are backed up by original research results. The chapter provided here in-depth look with all necessary theory and mathematical calculations. It will be perfect for laymen and developers as it will combine both advanced and introductory material to form an argument for what machine learning could achieve in the future. It will provide a vision on future areas of application and their approach in detail. Therefore, this book will be immensely beneficial for the academicians, researchers and industry project managers to develop their new project and thereby beneficial for mankind. Original research and review works with model and build Robotics applications using Machine learning are included as chapters in this book.