Dynamic model of Malware propagation based on tripartite graph and spread influence
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ORIGINAL PAPER
Dynamic model of Malware propagation based on tripartite graph and spread influence Tun Li
· Yanbing Liu · Xinhong Wu · Yunpeng Xiao · Chunyan Sang
Received: 19 December 2019 / Accepted: 31 August 2020 © Springer Nature B.V. 2020
Abstract The large-scale use of the Internet brings the problem of the rapid spread of computer malware over the network. Aiming at the relationship between malware, propagation paths and users in network propagation, this paper proposes a perception propagation model of computer malware based on a tripartite graph. First of all, aiming at the driving and influence of malware, propagation paths and users’ association in the network, this paper introduces a malware propagation tree structure, constructs two bipartite graphs of malware–propagation paths and propagation paths– users, and takes the paths as a bridge to form a tripartite graph of malware, propagation paths and users. Second, aiming at the complexity of the driving factors of malware in the process of propagation and the multiplicity of influence, by introducing a Cross-iteration Scoring mechanism of tripartite graph and influencing quantification algorithm, a method to measure the influence of malware propagation is proposed. At the same time, it uses multiple linear regression to uniformly quantify the impact. Finally, considering the polymorphism in the process of computer malware propagation, time T. Li (B)· Y. Liu · X. Wu · Y. Xiao · C. Sang College of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, China e-mail: [email protected] T. Li Chongqing Engineering Lab Internet&Information Security, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
slicing and infection state refinement are introduced. Based on the traditional propagation model, the infection state is divided into the normal infection state and the high infection state, and the tripartite iterative algorithm and the influence power method are comprehensively considered. A novel propagation dynamic model of malware is proposed. Experiments show that the model can not only discover the spread situation of malware in the network, but also explore the relationship between malware, propagation paths and users and their influence on the spread situation. Keywords Malware · Tripartite graph · Cross-iteration Scoring · Spread situation
1 Introduction With the rapid development of network technology over the past few decades, malware like viruses and worms poses a serious threat to the reliability, integrity and availability of computers, and it can spread through the Internet and infect millions of computers and mobile phones [1]. The diversified propagation pathways in complex networks and the complex application environment bring great convenience to the spread and diffusion of malware [2] and pose great threat to the security of the network system and hosts on the network [3]. Therefore, it is of great research significance to analyze the propagation path and situ
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