Presents the emerging technologies and applications of computational intelligence for the law enforcement of the Dark Web. The book features analysis into cybercrime data, examples of the application of computational intelligence in the Dark Web, and provides future opportunities for growth in the field.

The Dark Web is a known hub that hosts myriad illegal activities behind the veil of anonymity for its users. For years now, law enforcement has been struggling to track these illicit activities and put them to an end. However, the depth and anonymity of the Dark Web has made these efforts difficult, and as cyber criminals have more advanced technologies available to them, the struggle appears to only have the potential to worsen. Law enforcement and government organizations also have emerging technologies on their side, however. It is essential for these organizations to stay up to date on these emerging technologies, such as computational intelligence, in order to put a stop to the illicit activities and behaviors presented in the Dark Web. Using Computational Intelligence for the Dark Web and Illicit Behavior Detection presents the emerging technologies and applications of computational intelligence for the law enforcement of the Dark Web. It features analysis into cybercrime data, examples of the application of computational intelligence in the Dark Web, and provides future opportunities for growth in this field. Covering topics such as cyber threat detection, crime prediction, and keyword extraction, this premier reference source is an essential resource for government organizations, law enforcement agencies, non-profit organizations, politicians, computer scientists, researchers, students, and academicians.

Inside the Dark Web provides a broad overview of emerging digital threats and computer crimes, with an emphasis on cyberstalking, hacktivism, fraud and identity theft, and attacks on critical infrastructure. The book also analyzes the online underground economy and digital currencies and cybercrime on the dark web. The book further explores how dark web crimes are conducted on the surface web in new mediums, such as the Internet of Things (IoT) and peer-to-peer file sharing systems as well as dark web forensics and mitigating techniques. This book starts with the fundamentals of the dark web along with explaining its threat landscape. The book then introduces the Tor browser, which is used to access the dark web ecosystem. The book continues to take a deep dive into cybersecurity criminal activities in the dark net and analyzes the malpractices used to secure your system. Furthermore, the book digs deeper into the forensics of dark web, web content analysis, threat intelligence, IoT, crypto market, and cryptocurrencies. This book is a comprehensive guide for those who want to understand the dark web quickly. After reading Inside the Dark Web, you’ll understand The core concepts of the dark web. The different theoretical and cross-disciplinary approaches of the dark web and its evolution in the context of emerging crime threats. The forms of cybercriminal activity through the dark web and the technological and "social engineering" methods used to undertake such crimes. The behavior and role of offenders and victims in the dark web and analyze and assess the impact of cybercrime and the effectiveness of their mitigating techniques on the various domains. How to mitigate cyberattacks happening through the dark web. The dark web ecosystem with cutting edge areas like IoT, forensics, and threat intelligence and so on. The dark web-related research and applications and up-to-date on the latest technologies and research findings in this area. For all present and aspiring cybersecurity professionals who want to upgrade their skills by understanding the concepts of the dark web, Inside the Dark Web is their one-stop guide to understanding the dark web and building a cybersecurity plan.

The University of Arizona Artificial Intelligence Lab (AI Lab) Dark Web project is a long-term scientific research program that aims to study and understand the international terrorism (Jihadist) phenomena via a computational, data-centric approach. We aim to collect "ALL" web content generated by international terrorist groups, including web sites, forums, chat rooms, blogs, social networking sites, videos, virtual world, etc. We have developed various multilingual data mining, text mining, and web mining techniques to perform link analysis, content analysis, web metrics (technical sophistication) analysis, sentiment analysis, authorship analysis, and video analysis in our research. The approaches and methods developed in this project contribute to advancing the field of Intelligence and Security Informatics (ISI). Such advances will help related stakeholders to perform terrorism research and facilitate international security and peace. This monograph aims to provide an overview of the Dark Web landscape, suggest a systematic, computational approach to understanding the problems, and illustrate with selected techniques, methods, and case studies developed by the University of Arizona AI Lab Dark Web team members. This work aims to provide an interdisciplinary and understandable monograph about Dark Web research along three dimensions: methodological issues in Dark Web research; database and computational techniques to support information collection and data mining; and legal, social, privacy, and data confidentiality challenges and approaches. It will bring useful knowledge to scientists, security professionals, counterterrorism experts, and policy makers. The monograph can also serve as a reference material or textbook in graduate level courses related to information security, information policy, information assurance, information systems, terrorism, and public policy.

This edited volume explores the fundamental aspects of the dark web, ranging from the technologies that power it, the cryptocurrencies that drive its markets, the criminalities it facilitates to the methods that investigators can employ to master it as a strand of open source intelligence. The book provides readers with detailed theoretical, technical and practical knowledge including the application of legal frameworks. With this it offers crucial insights for practitioners as well as academics into the multidisciplinary nature of dark web investigations for the identification and interception of illegal content and activities addressing both theoretical and practical issues.

The important and rapidly emerging new field known as 'cyber threat intelligence' explores the paradigm that defenders of computer networks gain a better understanding of their adversaries by understanding what assets they have available for an attack. In this book, a team of experts examines a new type of cyber threat intelligence from the heart of the malicious hacking underworld - the dark web. These highly secure sites have allowed anonymous communities of malicious hackers to exchange ideas and techniques, and to buy/sell malware and exploits. Aimed at both cybersecurity practitioners and researchers, this book represents a first step toward a better understanding of malicious hacking communities on the dark web and what to do about them. The authors examine real-world darkweb data through a combination of human and automated techniques to gain insight into these communities, describing both methodology and results.

"The reference book will show the depth of Darkweb Environment by highlighting the Attackers techniques, crawling of hidden contents, Intrusion detection using advance algorithms, TOR Network structure, Memex search engine indexing of anonymous contents at Online Social Network, and more"--