Presenting a Metric-Based Model for Malware Detection and Classification

Nowadays, malware is a known term in the cyber world, which has been created with the bad intents of spying, sabotage, changing, deleting information, and disordering. So the enormous direct and indirect costs carried by companies and organizations and its bad effects on their normal and commercial operation are undeniable. Until now, different approaches have been suggested for malware detection and classification. These approaches are divided into three groups of signature-based detections, behavior-based detection, and heuristics. Each one can be applied as static, dynamic (virtually simulation) or a mixture of both. Unfortunately, present methods aren’t efficient anymore. In this article, based on the malware behaviors, nine metrics are introduced according which a method for their detection and a model for their classification are represented

Keywords:

malware , malware metrics , metric's classification , metric-based model , Fuzzy AHP