Towards Fully Integrated Real-time Detection Framework for Online Contents Analysis - RED-Alert Approach

Naqvi, S. and Williams, Ian and Enderby, S. and Pollner, P. and Abel, D. and Biescas, B. and Garcia, O. and Florea, M. (2019) Towards Fully Integrated Real-time Detection Framework for Online Contents Analysis - RED-Alert Approach. In: IEEE European Symposium on Security and Privacy 2019, 17-20 June 2019, Sweden.

BCU_RED-Alert_Article.pdf - Accepted Version

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Social media is extensively used nowadays and is gaining popularity among the users with the increasing growth in the network capacity, connectivity, and speed. Moreover, affordable prices of data plans, especially mobile data packages, have considerably increased the use of multimedia by different users. This includes terrorists who use social media platforms to promote their ideology and intimidate their adversaries. It is therefore very important to develop automated solutions to semantically analyse online contents to assist law enforcement agencies in the preventive policing of online activities. A major challenge for the social media forensic analysis is to preserve the privacy of citizens who use online social networking platforms. This paper presents results of European H2020 project RED-Alert that aims to enable secure and privacy preserving data processing; hence the malicious content and the corresponding personality can be ethically tracked. We have mined seven social media channels for content and providing support for ten languages for analysis. Our proposed solution is designed to ensure security and policing of online contents by detecting terrorist material. We have used social network analysis, speech recognition, face and object detection besides audio event detection to extract information from online sources that are fed in a complex event processor. We have discussed the challenges and prospects of this work especially the need of analysing online contents while respecting European and national data protection laws notably GDPR.

Item Type: Conference or Workshop Item (Paper)
Additional Information: DOI: 10.1109/EuroSPW.2019.00035 ISBN: 978-1-7281-3027-9 © 2019 IEEE.  Personal use of this material is permitted.  Permission from IEEE must be obtained for all other uses, in any current or future media, including eprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works
6 May 2019Accepted
19 August 2019Published Online
Uncontrolled Keywords: Contents analysis, social network analysis, multimedia forensics, complex event processing, data protection
Subjects: CAH11 - computing > CAH11-01 - computing > CAH11-01-01 - computer science
Divisions: Faculty of Computing, Engineering and the Built Environment
Faculty of Computing, Engineering and the Built Environment > School of Computing and Digital Technology
Depositing User: Syed Naqvi
Date Deposited: 29 Jul 2019 10:17
Last Modified: 22 Mar 2023 12:01

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