TENSOR: retrieval and analysis of heterogeneous online content for terrorist activity recognition

AKHGAR, Babak, BERTRAND, Piere, CHANANOULI, Christina, DAY, Tony, GIBSON, Helen, KAVALLIEROS, Dimitrios, KOMPASTSIARIS, Ioannis, KYRIAKOU, Eva, LEVENTAKIS, George, LISSARIS, Euthimios, MILLE, Simon, TSIKRIKA, Theodora, VROCHIDIS, Stefanos and WILLIAMSON, Una (2017). TENSOR: retrieval and analysis of heterogeneous online content for terrorist activity recognition. In: Proceedings Estonian Academy of Security Sciences, 16 : From Research to Security Union. Estonian Academy of Security Sciences, 33-82.

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    Abstract

    The proliferation of terrorist generated content online is a cause for concern as it goes together with the rise of radicalisation and violent extremism. Law enforcement agencies (LEAs) need powerful platforms to help stem the influence of such content. This article showcases the TENSOR project which focusses on the early detection of online terrorist activities, radicalisation and recruitment. Operating under the H2020 Secure Societies Challenge, TENSOR aims to develop a terrorism intelligence platform for increasing the ability of LEAs to identify, gather and analyse terrorism-related online content. The mechanisms to tackle this challenge by bringing together LEAs, industry, research, and legal experts are presented.

    Item Type: Book Section
    Additional Information: ISSN: 2236-6006 (online)
    Research Institute, Centre or Group - Does NOT include content added after October 2018: Cultural Communication and Computing Research Institute > Communication and Computing Research Centre
    Departments - Does NOT include content added after October 2018: Faculty of Science, Technology and Arts > Department of Computing
    Page Range: 33-82
    Depositing User: Helen Gibson
    Date Deposited: 21 Dec 2017 11:17
    Last Modified: 14 Jan 2019 16:15
    URI: http://shura.shu.ac.uk/id/eprint/17411

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