구글 ‘Tensor Flow’를 이용한 웹사이트 악성 코드 유포지 위험도 분석 시스템 연구

Abstract

Recently, with the development of the Internet, the spread of malicious codes using the Internet is one of the serious cyber threats, and the malicious code distribution technology applied by the detection bypass technique is rapidly developing, and researches for detecting and analyzing this are being actively carried out. However, existing malicious code distribution webpage detection system is based on signature, so obfuscated malicious JavaScript is almost impossible to detect, and there is a limitation that analysts have to constantly update detection pattern after detection. To overcome these limitations, we propose an intelligent malicious code distributed web page detection system using machine learning that can effectively analyze and detect intelligent malicious code distributed web pages.