Anzeige
Erschienen in:
2012 | OriginalPaper | Buchkapitel
60. Malware Classification Methods Using API Sequence Characteristics
verfasst von : Kyoung-Soo Han, In-Kyoung Kim, Eul Gyu Im
Erschienen in: Proceedings of the International Conference on IT Convergence and Security 2011
Verlag: Springer Netherlands
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
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.