An effective framework of behavior detection-advanced static analysis for malware detection
Maya Hilda Lestari Louk, Hyotaek Lim, Hoon Jae Lee, Mohammed Atiquzzaman · 2014
The recent development of malwares is rapidly progressing and intruders are getting better at concealing malwares to deceive users while researchers are developing security systems. One of the methods which is commonly used is behavior detection. In this paper, a more efficient behavior detection method and the framework of intrusion malware security system is presented. In addition, the implementation of the prototype and the result of the discussion is presented under advanced static analysis which is added PE Header study. Our proposed framework will (1) contribute to improve the security system for malware detection, especially to detect sophisticated malware, (2) show the effectiveness of behavior detection to memory performance, and (3) how advanced static analysis matches the algorithm for malware detection.