A static heuristic approach to detecting malware targets

摘要: Nowadays malware writers usually employ several obfuscation techniques to evade detection. The number of variants detected each day has been increasing significantly. Unfortunately traditional detection approaches such as signature scanning are becoming inefficient detect malwares. Researches show that these obfuscations make some anomalies in Portable Executable files. In this paper, by focusing on important static heuristic features and fuzzy classification algorithms, we tried malwares packed addition, used preprocessing anomaly exceptions benign files improved our results. experimental results, using over 63000 file samples, indicate the proposed detector achieves high results with low false positive negative rates. Furthermore, new samples had undetectable for many years antivirus products custom packers, system works well unknown too. Copyright © 2015 John Wiley & Sons, Ltd.