Malware propagation analysis in message-recallable online social networks
Yijin Chen, Yuming Mao, Supeng Leng, Yunkai Wei, Yuchen Chiang · 2017
The powerful information diffusion ability of online social networks (OSNs) attracts many attackers to spread malware, because malware can fiercely spread among massive active users with close social relationship in OSNs. A message-recallable function in user profile of modern OSNs can delete messages containing malicious link, and stop malware spreading. However, existing works on malware propagation models have not concerned the new message-recallable mechanism (MRM). This paper proposes a novel malware spread model to analyze the performance of malware propagation in OSNs with MRM. For analyzing the malware spread model, we carry out theoretical derivation to obtain key metrics, including infection rate, recalling rate, and epidemic threshold. Numerical analysis and simulation are conducted to validate the accuracy of the proposed model. The proposed malware spread model with theoretical metrics can provide a guidance to design highly efficient network defense schemes for emerging message-recallable OSNs.