ANALYSIS OF MACHINE LEARNING METHODS ON MALWARE DETECTION

被引：0

作者：

Aydogan, Emre ^{[1
]}

Sen, Sevil ^{[1
]}

机构：

[1] Hacettepe Univ, Bilgisayar Muhendisligi Bolumu, Ankara, Turkey

来源：

2014 22ND SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU) | 2014年

关键词：

malware analysis and detection; machine learning;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Nowadays, one of the most important security threats are new, unseen malicious executables. Current anti-virus systems have been fairly successful against known malicious softwares whose signatures are known. However they are very ineffective against new, unseen malicious softwares. In this paper, we aim to detect new, unseen malicious executables using machine learning techniques. We extract distinguishing structural features of softwares and, employ machine learning techniques in order to detect malicious executables.

引用

页码：2066 / 2069

页数：4

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