Automatic Detection Model of Malware Signature for Anti-virus Cloud Computing

Security vendors are facing a serious problem of defeating the complexity of malwares. With the popularity and the variety of malware over the Internet, generating their signatures for detecting via anti-virus (AV) scan engines becomes an important reactive security function. However, AV security products consume much of the PC memory and resources due to their large signature files. AV cloud computing becomes a popular solution for this problem. In this paper, a novel automatic malware signature discovery system for AV cloud (AMSDS) is proposed to generate malware signatures from both static and dynamic aspects. Our experiment on millions-scale samples indicates that AMSDS outperforms most automatic signature generation techniques of both industry and academia. The detection model of malware signature can provides research thinking for anti-virus technology to improve and enhance, especially on detecting and preventing unknown viruses or malware signature.