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

Tools

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. [Book Section]

[+][-]

Documents

17411:311531
17411:311532

[+][-]

17411:311531

Preview

PDF
TENSOR_EASS.pdf - Published Version
Available under License All rights reserved.

Download (2MB) | Preview

17411:311532

Other (Acceptance Email)
TENSOR TENSOR article submission.msg - Other
Restricted to Repository staff only

Download (94kB)

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.

More Information

Official URL:

https://digiriiul.sisekaitse.ee/handle/123456789/2...

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

ISBN: