Soft Computing has been widely used in Information Security. Fuzzy Logic represents a particular interest since it is capable of not only classification, but also human-understandable representation of the information. Multiple studies show the applicability of the fuzzy logic in malware detection, yet the accuracy may not be sufficiently good classification accuracy due to the parameters of fuzzy sets. The talk will be about the adaptive Hybrid Neuro-Fuzzy methods that uses Self-Organizing Map to automatically extract parameters of fuzzy patches for the Mamdami-type classification rules. Moreover, the study of possible representation and visualization for reasoning will be given.