A Malware Classification Model Using Fuzzy Inference System (MTCFIS)

Information Security has become a major challenge in the present years due to the continuous global information technological development. It means Information and communication (ICT) environment are frequently exposed to various types of malware threats which can cause different types of damages that might lead to significant financial losses. ICT,s security damages can range from small losses to very high information infrastructure destruction. Currently, organizations are struggling to understand what the malware threats to their information assets are and how to obtain the necessary means to combat them which continues to pose a challenge. In this paper we propose a fuzzy inference system for threat classification to improve organization staff understanding of security threats. This mode called MTCFIS which allows us to classify the malware threats as a class based on their impact severity on organization assets. The paper addresses required criteria for malwares classification and gives a review of malwares and fuzzy inference systems. The proposed model supports all malware threats classification principles and helps organizations implement their security strategies to deal with malware threats.

کلیدواژه ها:

Fuzzy inference systems ، Malware ، classification ، Threat