Paper Title
A Survey on Dynamic Identification of Malicious Obfuscated Java Scripts

Abstract
In recent scenario, the JavaScript has become one of the leading choices for attackers to implement their attacks and infecting users with malicious software. Static analysis fails to protect from this threat, In contrast, the dynamic analysis at run-time has proven to be effective. During the execution of the code, damage may already occur for this early detection is difficult for protection. In this paper, we survey early detection system which identifies malicious activities in JavaScripts. In which uses machine learning techniques for accuracy and the time of detection. Keywords- SVM, Obfuscated JavaScript, Static Analysis, Dynamic Analysis.