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MPPM: Malware propagation and prevention model in online SNS

机译:MPPM:在线SNS中的恶意软件传播和预防模型

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摘要

With the pervasiveness of online social network service (SNS), many people express their views and share information with others on them, and the information propagation model of online SNS has attracted considerable interest recently. However, the flourish of information propagation model in online SNS still faces many challenges, especially considering more and more malicious software's propagation in SNS. In this paper, we proposed a malware propagation and prevention model based on the propagation probability model, called MPPM, for online SNS. With this model, we can describe the relationships among malware propagation, habits of users and malware detection in online SNS. In specific, based on characteristics of online SNS, we define users' states and the rules of malware propagation with dynamics of infectious disease; then, we introduce the detection factor to affect the propagation of malwares, and present the malwares propagation and prevention in online SNS by dynamic evolution equations; finally, we analyze the factors which influence the malware propagation in online SNS. Detailed analysis and simulation demonstrate that the MPPM model can precisely describe the process of malware's propagation and prevention in online SNS.
机译:随着在线社交网络服务(SNS)的普遍性,许多人表达了他们的观点并与其他人共享信息,并且最近在线SNS的信息传播模型引起了相当大的利益。然而,在线SNS中信息传播模型的蓬勃发展仍然面临着许多挑战,特别是考虑越来越多的恶意软件在SNS中的传播。在本文中,我们提出了一种基于传播概率模型的恶意软件传播和预防模型,称为MPPM,用于在线SNS。使用此模型,我们可以描述恶意软件传播,用户习惯和在线SNS中的恶意软件检测的关系。具体而言,基于在线SNS的特征,我们定义了用户的状态和与传染病的动态的恶意软件传播规则;然后,我们介绍了影响恶意的传播的检测因素,并通过动态演化方程介绍在线SNS中的恶意传播和预防;最后,我们分析了影响在线SNS中恶意软件传播的因素。详细分析和仿真表明,MPPM模型可以精确描述在线SNS中恶意软件的传播和预防过程。

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