Malware Propagation in Large-Scale Networks

Abstract

Malware is prevalent in networks, and creates a condemnatory warning to network safety. However, we have very little grasp of malware performance in networks till date. In this project, we scrutinize how malware spread in networks from a global viewpoint. We construct the problem, and organize an accurate two layer outbreak model for malware spreading from network to network. Based on the submitted model, our inspection specifies that the dispensation of a given malware follows exponential dispensation, power law dispensation with a short exponential tail, and power law dispensation at its primarily, late and last phases, . Large Scale tests have been executed between two real-world comprehensive malware data sets and the outcome confirm our conceptual detections.