Malware classification methods using API sequence characteristics

Abstract

Malware is generated to gain profits by attackers, and it infects many users' computers. As a result, attackers can acquire private information such as login IDs, passwords, e-mail addresses, cell-phone numbers and banking account numbers from infected machines. Moreover, infected machines can be used for other cyber-attacks such as DDoS attacks, spam e-mail transmissions, and so on. The number of new malware discovered every day is increasing continuously because the automated tools allow attackers to generate the new malware or their variants easily. Therefore, a rapid malware analysis method is required in order to mitigate the infection rate and secondary damage to users. In this paper, we proposed a malware variant classification method using sequential characteristics of API used, and described experiment results with some malware samples.