Recognizing and Handling the Malware Propagation in Large Scale Networks
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Date
2017-08-18T12:12:52Z
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Abstract
Malware is pervasive in networks, and poses a critical threat to network security. However, many people have very limited understanding of malware behavior in networks to date. The aim is to investigate how malware propagates in networks from a global perspective. The problem is formulated, and a rigorous two layer epidemic model for malware propagation from network to network is established. Based on the proposed model, the analysis indicates that the distribution of a given malware follows exponential distribution, power law distribution with a short exponential tail, and power law distribution at its early, late and final stages, respectively. Extensive experiments have been performed through two real-world global scale malware data sets, and the results confirm theoretical findings.
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Shobhita G H, Recognizing and Handling the Malware Propagation in Large Scale Networks, 1NH13IS087, Shishir Umesh