An Approach to Identify Vulnerable Features of Instant Messenger

Swift proliferation in Instant Messaging (IM) applications, installed on Smartphone, has made it a target of the attacker to conduct crimes such as cyber stalking, threatening etc. It is possible to exploit Instant Messaging applications, owing to the presence of vulnerabilities such as sensitive data capture, weak cryptography etc. It has fuelled the need of conducting forensic analysis of IM applications through classifying these vulnerabilities. This paper focuses on performing forensic analysisx of IM Application on Android platform by identifying and classifying vulnerabilities such as sensitive data capture, weak cryptography etc. An approach is proposed using Machine Learning Methodology combined with the Genetic Algorithm to conduct forensic analysis. Further the developed approach has been applied on Line messenger to test its' accuracy. It is examined that 12% features in Line Messenger are vulnerable.