WSEAS Transactions on Information Science and Applications
Print ISSN: 1790-0832, E-ISSN: 2224-3402
Volume 15, 2018
Suspicious Call Detection Using Bayesian Network Approach
Authors: , , ,
Abstract: The rapid advancements in the fast and rapidly growing field of information and communication technologies (ICT’s) has lead us to new thinking paradigm and it is being implemented in all walks of life including business, finance, health, management, engineering, basic sciences, sports, social sciences and many other domains. There are many advantages of speedy growth of internet and mobile phones in the society and people are taking full advantage of them. However this technology is widely used by the criminals for the execution of criminal or terrorist activities. The state of Pakistan is going through a period where they are crushing criminal and terrorist networks throughout the country. There are number of terrorist and criminal activities in the last few years. This study focuses on the use of related equipment like mobile phone, SIM’s etc. in criminal or terrorist activities. We have analyzed call detail records (CDR) collected from tower data of five mobile companies by using geo-fencing approach. The classification of suspicious call detection and identification is done by using Bayesian classifier approach. In the research document, the researcher exhibits approaches for establishing Bayesian systems from previous information and review Bayesian techniques for improvisation of these models. We encapsulate approaches for structuring and learning parameters in Bayesian system, including various methods to learn from Bayesian database.
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Keywords: Information and communication technology (ICT), Bayesian Network, call data record (CDR), criminal network, geo-fencing, suspicious call detection, geo-fence
Pages: 37-49
WSEAS Transactions on Information Science and Applications, ISSN / E-ISSN: 1790-0832 / 2224-3402, Volume 15, 2018, Art. #5