A new method of fuzzy patches construction in Neuro-Fuzzy for malware detection

DOI

10.2991/ifsa-eusflat-15.2015.27How to use a DOI?

Keywords

Malware detection, neuro-fuzzy, digital forensics, optimization

Abstract

Soft Computing is being widely used in Information Security applications. Particularly, Neuro-Fuzzy approach provides a classification with humanunderstandable rules, yet the accuracy may not be sufficiently high. In this paper we seek for an optimal fuzzy patch configuration that uses elliptic fuzzy patches to automatically extract parameters for the Mamdami-type rules. We proposed a new method based on X2 test of data to estimate rotatable patch configuration together with Gaussian membership function. This method has been tested on the automated malware analysis with accuracy up to 92%. Further on, it can find an application in Digital Forensics.

Copyright

© 2015, 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  - Andrii Shalaginov
AU  - Katrin Franke
PY  - 2015/06
DA  - 2015/06
TI  - A new method of fuzzy patches construction in Neuro-Fuzzy for malware detection
BT  - Proceedings of the 2015 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and Technology
PB  - Atlantis Press
SP  - 170
EP  - 177
SN  - 1951-6851
UR  - https://doi.org/10.2991/ifsa-eusflat-15.2015.27
DO  - 10.2991/ifsa-eusflat-15.2015.27
ID  - Shalaginov2015/06
ER  -