Dark Web Spiders
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Dark Web Spiders
Author: R. Julian Hafner
language: en
Publisher: Australian Self Publishing Group
Release Date: 2025-08-01
They don’t follow the law. They hunt those who break it. In Dark Web Spiders, the explosive sequel to Ordeal Therapy by R. Julian Hafner, a covert five-person team uses the Internet’s Dark Web to track down the world’s most dangerous criminals and wage a relentless real life war against them. Their mission cuts through cybercrime, people smuggling and the darkest corners of the human soul. As they dig deeper, the stakes rise: money laundering, art theft and weaponised deep fakes give way to even more disturbing threats — illegal organ harvesting, secretive transhumanist labs and cults that kill for power and pleasure. Watching from the shadows is an enemy who will stop at nothing to destroy them. But this team does not flinch. From séances gone wrong to a dominatrix’s downfall and a murder in a Gypsy camp, they strike hard, fast and without apology. Gritty, fast paced and unflinching, Dark Web Spiders drops you into a shadow war where justice is personal and survival is never guaranteed. The dark web grows stronger. The war will go on.
DARK WEB
Deep Web, also known as "Deepnet," the "Invisible Web," the "Undernet" or the "hidden Web," are parts of the Internet that are not considered part of the "surface web," or the portion of the World Wide Web that is indexed by conventional search engines. Many deep websites are not indexed because they use dynamic databases that are devoid of hyperlinks and can only be found by performing an internal search query.The Dark Web is the part of the Deep web it mainly contains information about hackers, illegal sexual videos, guns, and drugs, so this book contains all these information's relevant to Dark web and secrets and creepy stories about Dark Web.
Dark Web
Author: Hsinchun Chen
language: en
Publisher: Springer Science & Business Media
Release Date: 2011-12-17
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.