Ransomeware classification using fuzzy neural network algorithm

Abstract

Traditional malware classification relies on known malware types and significantly large datasets labelled manually which limits its ability to recognize new malware classes. For unknown malware types or new variants of existing malware containing only a few samples each class, common classification methods often fail to work well due to severe over fitting. In this paper, we propose a new neural network structure called fuzzy neural network based algorithm for ransom ware classification. Malware classification with fuzzy neural network classifier yields 98% accuracy which means greater performance than classification with neural network.