Malicious JavaScript detection using machine learning

JavaScript has become a ubiquitous Web technology that enables interactive and dynamic Web sites. The widespread adoption, along with some of its properties allowing authors to easily obfuscate their code, make JavaScript an interesting venue for malware authors. In this survey paper, we discuss some of the difficulties in dealing with malicious JavaScript code, and go through some recent approaches to detect and classify malicious JavaScript code statically using machine learning methods [10, 11, 12].