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A Framework for Forensically Sound Harvesting the Dark Web
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
Stockholm University, Faculty of Social Sciences, Department of Computer and Systems Sciences.
2018 (English)In: Proceedings of the Central European Cybersecurity Conference 2018, Association for Computing Machinery (ACM), 2018, article id 13Conference paper, Published paper (Refereed)
Abstract [en]

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.

Place, publisher, year, edition, pages
Association for Computing Machinery (ACM), 2018. article id 13
Keywords [en]
Digital forensics, dark web, forensic soundness
National Category
Computer Sciences
Research subject
Computer and Systems Sciences
Identifiers
URN: urn:nbn:se:su:diva-164354DOI: 10.1145/3277570.3277584ISBN: 978-1-4503-6515-4 (electronic)OAI: oai:DiVA.org:su-164354DiVA, id: diva2:1279078
Conference
Central European Cybersecurity Conference 2018, Ljubljana, Slovenia, November 15 - 16, 2018
Available from: 2019-01-15 Created: 2019-01-15 Last updated: 2019-01-17Bibliographically approved

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CiteExportLink to record
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