Using Computational Intelligence for the Dark Web and Illicit Behavior Detection

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.

The many academic areas covered in this publication include, but are not limited to:

• Anomaly Detection
• Anonymous Training
• Crime Prediction
• Crime Recognition
• Cyber Security
• Cyber Threat Detection
• Dark Web Threat Evolution
• Darknet Traffic Analysis
• Facial Patterns Enhancement
• Fake Web Content
• Intimidation Comprehension
• IoT Botnet Detection
• Keyword Extraction