Defense against malware propagation in complex heterogeneous networks
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Defense against malware propagation in complex heterogeneous networks Soodeh Hosseini1,2 Received: 1 December 2019 / Revised: 25 August 2020 / Accepted: 31 August 2020 Ó Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract Devising appropriate defense strategies against malware propagation in complex networks with minimal budget is a challenging problem in research community. This paper studies and compares various immunization strategies such as random immunization, targeted immunization, acquaintance immunization and high-risk immunization to prevent the outbreak of malware. Also, three measures of node centrality (degree, closeness and betweenness) are taken into targeted immunization to slow down the malware propagation process. The malware propagation is modelled based on the susceptible–exposed–infected–recovered–susceptible with quarantine state (SEIRS-Q) epidemic model. Using numerical simulations, the model is verified with considering defense mechanisms in a synthetic (SFN) and a real (Facebook) network topology. The simulation results can help to better understand the effects of defense strategies against the malware propagation. The results show that the use of immunization and software diversity together are more effective than using each of them singly, in terms of reducing the density of infected node and halting malware propagation. Keywords Malware propagation Defense mechanisms Software diversity Immunization Heterogeneous networks
1 Introduction Nowadays, Malware has become a serious threat in the network security and communication network. The threats of malware such as worms, botnet, and virus can damage network security and social network safety [1]. Complex heterogeneous networks such as the Internet, the World Wide Web or the social networks often present high heterogeneity in their connectivity. These networks with high heterogeneity are often referred to as scale-free networks (SFNs), which show power-law degree distribution pðkÞ kc ð2\c 3Þ [2]. Across scientific domains and classes of networks, it is common to encounter the claim that most or all real-world networks are complex heterogeneous networks such as scale free networks [3]. These & Soodeh Hosseini [email protected] 1
Department of Computer Science, Faculty of Mathematics and Computer, Shahid Bahonar University of Kerman, Kerman, Iran
2
Mahani Mathematical Research Center, Shahid Bahonar University of Kerman, Kerman, Iran
networks are significantly prone to attacks and the persistence of malware infections because the connectivity fluctuations are very high in them. In order to controlling the outbreak of malware in complex heterogeneous networks, defense strategies such as immunization and software diversity are considered to prevent malware propagation in SFNs. Diversification is to generate different kinds of application software with similar behavior but with various structures [4, 5]. Therefore, diversification enhances the durability o
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