Abstract
In this paper, we propose a polymorphic viruses detection method based on support vector machine (SVM) in the Windows platform. Our approach rests on an analysis using the Windows API calling sequence that reflects the behavior of a particular piece of code. By extracting the variable-length system calling sequence or patterns in system calling sequence as the SVM training data and employing the ReliefF algorithm for estimating attributes previously obtained, then using cross-validation to experiment the arguments, the experimental results indicate that this method generates a relative small training data and higher accuracy than traditional ways which using fixed length of system calling sequence.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
