Automation Analytical Model of Familial Malware Based on Communication Features

DOI

10.2991/cimns-16.2016.3How to use a DOI?

Keywords

familial malware; communication features; automated analysis; feature extraction

Abstract

Up to date, the Internet industry has done a lot of research on malware analysis, which brings in effective malware detection. However, in terms of familial communication feature extraction and detection, a very mature product has yet to be seen. Given this situation, this paper tries to establish an automatic model for the analysis, extraction of familial communication features which is based on the family clustering results replay the communication traffic of the same family, classify and analyze communication features of each malware, extract the relatively stable hexadecimal common packet payload value, as the family communication features for network detection. Experimental results show that the proposed analytical can effectively identify the familial malware and its new variants.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Yiyang Wang
AU  - Shaoming Chen
AU  - Chongbin Wu
PY  - 2016/09
DA  - 2016/09
TI  - Automation Analytical Model of Familial Malware Based on Communication Features
BT  - Proceedings of the 2016 International Conference on Communications, Information Management and Network Security
PB  - Atlantis Press
SP  - 12
EP  - 15
SN  - 2352-538X
UR  - https://doi.org/10.2991/cimns-16.2016.3
DO  - 10.2991/cimns-16.2016.3
ID  - Wang2016/09
ER  -