Identification of Suspicious Activities in Chat Logs using Support Vector Machine and Optimization with Genetic Algorithm

Abstract

In the era of modern technology, the advancements in communication technology are leading to riveting trends in daily lives through instant messengers, social networking websites and many other popular communication technologies. Unfortunately, with this advancement the misuse of technology has also been proliferated which leads to the increase in suspicious activities. Some people misuse the technology to spread violence, share criminal activity, bullying other people and thereby enhances the suspicious content on the internet. The communication may be available in the form of text, audio or even in video format. In this research paper, text based chat logs are being used. Features from pre-processed data are extracted and bipartite graph is applied for the computation of feature values. The algorithm which is used is SVM (Support Vector Machine) and the concept is optimized using Genetic algorithm.

Authors and Affiliations

Amandeep Singh Khangura, Maninderpal Singh Dhaliwal, Mansi Sehgal

Keywords

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  • EP ID EP24827
  • DOI -
  • Views 412
  • Downloads 16

How To Cite

Amandeep Singh Khangura, Maninderpal Singh Dhaliwal, Mansi Sehgal (2017). Identification of Suspicious Activities in Chat Logs using Support Vector Machine and Optimization with Genetic Algorithm. International Journal for Research in Applied Science and Engineering Technology (IJRASET), 5(7), -. https://europub.co.uk/articles/-A-24827