Models for the Detection of Malicious Intent People in Society

Models for the Detection of Malicious Intent People in Society

Preetish Ranjan (Indian Institute of Information Technology, Allahabad, India), Vrijendra Singh (Indian Institute of Information Technology, Allahabad, India), Prabhat Kumar (National Institute of Technology, Patna, India) and Satya Prakash (Indian Institute of Information Technology, Allahabad, India)
Copyright: © 2018 |Pages: 12
DOI: 10.4018/IJDCF.2018070102

Abstract

This article describes how in less than two decades, internet in mobile phones has grown from a curiosity to an essential element of modern life. Although, this mind-boggling growth has no doubt facilitated international commerce, trade, and travel, it is also being used in the planning and coordination of criminal activities. These types of attacks are often referred to as socio-technical attacks. These attacks are targeted at these sensitive points to society or national security and may have a devastating impact. Often, organized, sponsored, and trained groups are involved to disguise the intelligence system, deployed for the detection of such attacks. Prior detection of such attacks may reduce its impact. In this article, the authors have developed an efficient model to detect malicious node in huge and complex corpus of data associated with call detail record (CDR). This model analyses CDRs to identify covert nodes operating within society for malicious intent.
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Literature Review

The emergence of smart phone has made the communication more fast and complex. Inexpensive cost of technology and corresponding service encourages users to connect with multiple motives. Service providers analyze different attributes of CDR to identify and evaluate customer base (Bianchi, dOHeureuse, & Niccolini, 2011; Kianmehr & Alhajj, 2009). Marketing professionals discover shift of customers from one product to other. Seungjae et al. devised pricing strategy of product by analyzing calling pattern obtained from CDR (Shin, Park, Lee, & Lee, 1998). Due to easy availability of mobile phones and SIM cards, they are readily used to plan high profile crimes such as kidnappings. It poses a challenging risk if these are being used in secretly. This has caused a rapid growth in research in the field under study. Markus Huber et al. studied socio-technical attacks as large scale spamming on social networking sites where they explored virality of information in destructive sense (Huber, Mulazzani, Schrittwieser, & Weippl, 2010). Integrity of message may be changed and may be made viral by some malicious intent people. They were unable to identify the holistic insight within social network. Mohammad Reza et al. and Sharad Goel et al. observed that it not only the content but structure of social network is also equally responsible for the diffusion of information in network (Faghani, Saidi, & Nguyen; Goel, Anderson, Hofman, & Watts).

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