A New Profiling Framework In Identifying Cyber Violent Extremism Attack

• Main Author: Mohd Salleh, Nurhashikin
• Format: Thesis
• Language: English; English
• Published: 2018
• Subjects: H Social Sciences (General); HV Social pathology. Social and public welfare
• Online Access: http://eprints.utem.edu.my/id/eprint/23328/1/A%20New%20Profiling%20Framework%20In%20Identifying%20Cyber%20Violent%20Extremism%20Attack.pdf; http://eprints.utem.edu.my/id/eprint/23328/2/A%20New%20Profiling%20Framework%20In%20Identifying%20Cyber%20Violent%20Extremism%20Attack.pdf; http://eprints.utem.edu.my/id/eprint/23328/; http://plh.utem.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=112735

Violent extremism has become a serious issue and an area of interest to government as it could leave difficult conditions to the nation. Violent extremism happens when someone chooses to carry out violent method and intent to cause harm to other. These groups of extremists aim to cause as much damage as possible when they intent to create harm to the target. Internet as the medium of communication has led to the formation of cyber communities which attracts violent extremism group. Recently, the violent extremism group uses the Internet as their platform to form online communities and launch their attack, these activities known as Cyber Violent Extremism (Cyber-VE). The ongoing increase in online activities by violent extremist groups along with the lack of mechanisms that can be used to identify violent extremism activity could be considered as a major problem. The threat of Cyber-VE is still on the rise and the existing mechanism do not seem to be reducing this attack. Therefore, the aim of this research is to develop a new profiling framework to help forensic investigators in identifying any activities that related to Cyber-VE attack. This done by integrating the classification of the Cyber-VE traces and the components of criminology theory. Prior to that, an analysis of the exiting profiling process is conducted to identify the process requirements in order to develop the profiling framework. After completing the analysis, an experimental design was setup to generate Cyber-VE traces classification. Traces classification is generated through the process of identifying, extracting and classifying traces. In order to identify the causes that leading to criminal behaviors, two types of criminology theory are used which are social learning theory and space transition theory. A combination of Social Learning Theory and Space Transition Theory was used to explain and identify the criminal behavior in which the criminal behavior will refer to Cyber-VE behavior. Then, both traces classification and criminology theory are integrated in order to develop the profiling framework. The proposed Cyber-VE profiling framework consists of three main processes which are data extraction and classification, Cyber-VE behavior identification, and Cyber-VE profile construction. This profiling framework is evaluated and validated to verify its capabilities in profiling Cyber-VE activities. In the experimental approach, the results from the dataset showed that profiling framework is capable to profile Cyber-VE activities using the proposed profiling framework. In expert view, the results showed that the proposed profiling framework is able to identify the activities that related to Cyber-VE attack.