نویسندگان
1 دانشگاه آزاد اسلامی، واحد بروجرد
2 دانشگاه علم و صنعت ایران
چکیده
کلیدواژهها
عنوان مقاله [English]
نویسندگان [English]
One of passive defence principles is the immunization unit against the attacks to computer systems. Large set of attacks is occurred by malware to computer systems. Performance of existing techniques should be evaluated against malware attacks. In this regards, one of the approaches in this area is to perform the managed attacks by the produced malwares through intelligent engines. Most of anti-malware products may apply the detection techniques based on binary signature code to identify the malware. A family of computer malware called as metamorphic exists whose signature has been changed in each generation through applying the obfuscation techniques so that they cannot be identified by binary malware signature based detection techniques. In this paper, a metamorphic engine has been presented on the basis of learning cellular automata. This engine is capable to confront the detection techniques according to codes statistical analysis due to its dynamic nature, identification ability and creation of safety program’s similar codes with high similarity rate. This engine could be a suitable tool for assessing the performance of existing systems to encounter the possible attacks.
کلیدواژهها [English]
)
