Abstract
With the development of software security technology, more and more malicious programs constantly uses new confusion and feature hiding techniques, the malware detection technology need to upgrade urgently. This paper presents a malware detection method based on sandbox, binary instrumentation and multidimensional feature extraction. We introduced the design and implementation of sandbox, feature extractor and the classifier. Finally, we merged multiple models and get a pretty well classifier for the malware detection.
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Wang, C., Ding, J., Guo, T., Cui, B. (2018). A Malware Detection Method Based on Sandbox, Binary Instrumentation and Multidimensional Feature Extraction. In: Barolli, L., Xhafa, F., Conesa, J. (eds) Advances on Broad-Band Wireless Computing, Communication and Applications. BWCCA 2017. Lecture Notes on Data Engineering and Communications Technologies, vol 12. Springer, Cham. https://doi.org/10.1007/978-3-319-69811-3_39
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DOI: https://doi.org/10.1007/978-3-319-69811-3_39
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