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A Framework for a Forensically Sound Harvesting the Dark Web

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Published:15 November 2018Publication History

ABSTRACT

The generative and transformative nature of the Internet which has become a synonym for the infrastructure of the contemporary digital society, is also a place where there are unsavoury and illegal activities such as fraud, human trafficking, exchange of control substances, arms smuggling, extremism, and terrorism. The legitimate concerns such as anonymity and privacy are used for proliferation of nefarious deeds in parts of the Internet termed as a deep web and a dark web. The cryptographic and anonymity mechanisms employed by the dark web miscreants create serious problems for the law enforcement agencies and other legal institutions to monitor, control, investigate, prosecute, and prevent the range of criminal events which should not be part of the Internet, and the human society in general. The paper describes the research on developing a framework for identifying, collecting, analysing, and reporting information from the dark web in a forensically sound manner. The framework should provide the fundamentals for creating a real-life system that could be used as a tool by law enforcement institutions, digital forensics researchers and practitioners to explore and study illicit actions and their consequences on the dark web. The design science paradigms is used to develop the framework, while international security and forensic experts are behind the ex-ante evaluation of the basic components and their functionality, the architecture, and the organization of the system. Finally, we discuss the future work concerning the implementation of the framework along with the inducement of some intelligent modules that should empower the tool with adaptability, effectiveness, and efficiency.

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    • Published in

      cover image ACM Other conferences
      CECC 2018: Proceedings of the Central European Cybersecurity Conference 2018
      November 2018
      109 pages
      ISBN:9781450365154
      DOI:10.1145/3277570

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      Publication History

      • Published: 15 November 2018

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      CECC 2018 Paper Acceptance Rate19of30submissions,63%Overall Acceptance Rate38of65submissions,58%

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