Malware prediction techniques: selection and implementation for integrated cyber evidence

Abstract

Recent studies have shown the negatives impact of malware attacks are increasing. To prevent malware attack in more proactive way, predictions of such attacks are needed. However, the quality and the accuracy of these predictions are determined by the applied techniques. In this paper, we report our findings on selecting and implementing such techniques in predicting malware attacks. For the selection process, we conducted a systematic review and searched over 5 major databases. 89 articles on malware predictions were finally included and prediction techniques are classified. As part of our on-going development project known as Integrated Cyber Evidence (ICE), we evaluated the selected technique using actual data of malware attacks. The results of evaluation had helped us to decide the final technique to be implemented in prediction module of ICE systems.