A dynamic method of detecting malicious scripts using classifiers - Nayeem, Khan; Jiwa, Abdullah; Adnan Shahid, Khan (American Scientific Publishers, 2017)
Due to the increasing importance of Internet in every aspect of our life, the World Wide Web which is accessed by end users through web browsers is becoming the next platform for criminal or individual with the malicious intent to conduct malicious activities either for personal or economic gains. Malicious scripts work as a primary source of infection for malicious software or also known as malware. This paper proposes an efficient method of detecting malicious scripts by employing an interceptor on the client side by using a set of supervised and unsupervised classifiers. The proposed method will be implemented to achieve high detection rate with low false alarms and minimal performance overheads. © 2017 American Scientific Publishers All rights reserved.