Implementation of a Security Model for Malware Based on Artificial Immune System

This research discusses intrusion detection systems based on computer networks and a model for the detection of malware using artificial immune system (AIS). The SIA has three main theories: the clonal selection, negative selection and network theory. This work used the ClonalG algorithm developed by Castro & Timmis (2002) [5] and implemented in Weka 3.6.4 for the intrusions detection in the KDD 1999 database. Preliminary results indicate good results, since was obtained 77.92% accuracy in the classification of threats using CLONALG algorithm, and 92.69% of accuracy by using CLONALG and feature selection of a total of 494,021 processed registers.