A new method of fuzzy patches construction in Neuro-Fuzzy for malware detection
Authors
Andrii Shalaginov, Katrin Franke
Corresponding Author
Andrii Shalaginov
Available Online June 2015.
- 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/).
Cite this article
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 -