An Approach to Detect Malware Snippets

Abstract

With the proliferation in the internet technologies malware attacks also growing to steal credentials, money laundering, to take control on victim machines etc. Kaspersky give first rank to Malicious URL in top 20 Web based malwares. Attacker design web based malware snippets in such a way to automatically modify on the fly through obfuscation techniques. Most web-based applications are real-time by nature, this has the effect of significantly shrinking the timescale in which detection and enforcement decisions must be made. Due to these challenge, detection of web based malware through static analysis technique is a crucial task. This work introduced an algebraic based semantic static analysis technique to fast the detection process.