Modeling the propagation of mobile malware on complex networks
•A complex-network-based model for mobile malware spread is newly developed.•The impact of network topology on malware spread is considered in the novel model.•We analyze the parameter sensitivity on the propagation threshold of the model.•Research results show networks with higher heterogeneity con...
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Veröffentlicht in: | Communications in nonlinear science & numerical simulation 2016-08, Vol.37, p.249-264 |
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creator | Liu, Wanping Liu, Chao Yang, Zheng Liu, Xiaoyang Zhang, Yihao Wei, Zuxue |
description | •A complex-network-based model for mobile malware spread is newly developed.•The impact of network topology on malware spread is considered in the novel model.•We analyze the parameter sensitivity on the propagation threshold of the model.•Research results show networks with higher heterogeneity conduce to malware spread.
In this paper, the spreading behavior of malware across mobile devices is addressed. By introducing complex networks to model mobile networks, which follows the power-law degree distribution, a novel epidemic model for mobile malware propagation is proposed. The spreading threshold that guarantees the dynamics of the model is calculated. Theoretically, the asymptotic stability of the malware-free equilibrium is confirmed when the threshold is below the unity, and the global stability is further proved under some sufficient conditions. The influences of different model parameters as well as the network topology on malware propagation are also analyzed. Our theoretical studies and numerical simulations show that networks with higher heterogeneity conduce to the diffusion of malware, and complex networks with lower power-law exponents benefit malware spreading. |
doi_str_mv | 10.1016/j.cnsns.2016.01.019 |
format | Article |
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In this paper, the spreading behavior of malware across mobile devices is addressed. By introducing complex networks to model mobile networks, which follows the power-law degree distribution, a novel epidemic model for mobile malware propagation is proposed. The spreading threshold that guarantees the dynamics of the model is calculated. Theoretically, the asymptotic stability of the malware-free equilibrium is confirmed when the threshold is below the unity, and the global stability is further proved under some sufficient conditions. The influences of different model parameters as well as the network topology on malware propagation are also analyzed. Our theoretical studies and numerical simulations show that networks with higher heterogeneity conduce to the diffusion of malware, and complex networks with lower power-law exponents benefit malware spreading.</description><identifier>ISSN: 1007-5704</identifier><identifier>EISSN: 1878-7274</identifier><identifier>DOI: 10.1016/j.cnsns.2016.01.019</identifier><language>eng</language><publisher>Elsevier B.V</publisher><subject>Asymptotic properties ; Complex network ; Computer simulation ; Malware ; Malware propagation ; Mathematical models ; Mobile network ; Network topology ; Networks ; Spreading ; Stability ; Thresholds</subject><ispartof>Communications in nonlinear science & numerical simulation, 2016-08, Vol.37, p.249-264</ispartof><rights>2016 Elsevier B.V.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c336t-4b889d123a7a51eefc7ed4e66b9aa4ca773c88f9373f5ee267f345ea833593383</citedby><cites>FETCH-LOGICAL-c336t-4b889d123a7a51eefc7ed4e66b9aa4ca773c88f9373f5ee267f345ea833593383</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.cnsns.2016.01.019$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3550,27924,27925,45995</link.rule.ids></links><search><creatorcontrib>Liu, Wanping</creatorcontrib><creatorcontrib>Liu, Chao</creatorcontrib><creatorcontrib>Yang, Zheng</creatorcontrib><creatorcontrib>Liu, Xiaoyang</creatorcontrib><creatorcontrib>Zhang, Yihao</creatorcontrib><creatorcontrib>Wei, Zuxue</creatorcontrib><title>Modeling the propagation of mobile malware on complex networks</title><title>Communications in nonlinear science & numerical simulation</title><description>•A complex-network-based model for mobile malware spread is newly developed.•The impact of network topology on malware spread is considered in the novel model.•We analyze the parameter sensitivity on the propagation threshold of the model.•Research results show networks with higher heterogeneity conduce to malware spread.
In this paper, the spreading behavior of malware across mobile devices is addressed. By introducing complex networks to model mobile networks, which follows the power-law degree distribution, a novel epidemic model for mobile malware propagation is proposed. The spreading threshold that guarantees the dynamics of the model is calculated. Theoretically, the asymptotic stability of the malware-free equilibrium is confirmed when the threshold is below the unity, and the global stability is further proved under some sufficient conditions. The influences of different model parameters as well as the network topology on malware propagation are also analyzed. Our theoretical studies and numerical simulations show that networks with higher heterogeneity conduce to the diffusion of malware, and complex networks with lower power-law exponents benefit malware spreading.</description><subject>Asymptotic properties</subject><subject>Complex network</subject><subject>Computer simulation</subject><subject>Malware</subject><subject>Malware propagation</subject><subject>Mathematical models</subject><subject>Mobile network</subject><subject>Network topology</subject><subject>Networks</subject><subject>Spreading</subject><subject>Stability</subject><subject>Thresholds</subject><issn>1007-5704</issn><issn>1878-7274</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><recordid>eNp9UMtOwzAQtBBIlMIXcPGRS4IdO7ZzAAlVvKQiLnC2HGdTXJI42CmFv8elnJFG2odmRruD0DklOSVUXK5zO8Qh5kUackITqgM0o0qqTBaSH6aeEJmVkvBjdBLjmiRiVfIZun7yDXRuWOHpDfAY_GhWZnJ-wL7Fva9dB7g33dYEwGlpfT928IUHmLY-vMdTdNSaLsLZX52j17vbl8VDtny-f1zcLDPLmJgyXitVNbRgRpqSArRWQsNBiLoyhlsjJbNKtRWTrC0BCiFbxkswirGyYkyxObrY-6YLPzYQJ927aKHrzAB-EzVVVBDOhJCJyvZUG3yMAVo9Bteb8K0p0bu09Fr_pqV3aWlCE6qkutqrIH3x6SDoaB0MFhoXwE668e5f_Q_rwXRf</recordid><startdate>201608</startdate><enddate>201608</enddate><creator>Liu, Wanping</creator><creator>Liu, Chao</creator><creator>Yang, Zheng</creator><creator>Liu, Xiaoyang</creator><creator>Zhang, Yihao</creator><creator>Wei, Zuxue</creator><general>Elsevier B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7TB</scope><scope>8FD</scope><scope>FR3</scope><scope>JQ2</scope><scope>KR7</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>201608</creationdate><title>Modeling the propagation of mobile malware on complex networks</title><author>Liu, Wanping ; Liu, Chao ; Yang, Zheng ; Liu, Xiaoyang ; Zhang, Yihao ; Wei, Zuxue</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c336t-4b889d123a7a51eefc7ed4e66b9aa4ca773c88f9373f5ee267f345ea833593383</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Asymptotic properties</topic><topic>Complex network</topic><topic>Computer simulation</topic><topic>Malware</topic><topic>Malware propagation</topic><topic>Mathematical models</topic><topic>Mobile network</topic><topic>Network topology</topic><topic>Networks</topic><topic>Spreading</topic><topic>Stability</topic><topic>Thresholds</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Liu, Wanping</creatorcontrib><creatorcontrib>Liu, Chao</creatorcontrib><creatorcontrib>Yang, Zheng</creatorcontrib><creatorcontrib>Liu, Xiaoyang</creatorcontrib><creatorcontrib>Zhang, Yihao</creatorcontrib><creatorcontrib>Wei, Zuxue</creatorcontrib><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>Communications in nonlinear science & numerical simulation</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Liu, Wanping</au><au>Liu, Chao</au><au>Yang, Zheng</au><au>Liu, Xiaoyang</au><au>Zhang, Yihao</au><au>Wei, Zuxue</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Modeling the propagation of mobile malware on complex networks</atitle><jtitle>Communications in nonlinear science & numerical simulation</jtitle><date>2016-08</date><risdate>2016</risdate><volume>37</volume><spage>249</spage><epage>264</epage><pages>249-264</pages><issn>1007-5704</issn><eissn>1878-7274</eissn><abstract>•A complex-network-based model for mobile malware spread is newly developed.•The impact of network topology on malware spread is considered in the novel model.•We analyze the parameter sensitivity on the propagation threshold of the model.•Research results show networks with higher heterogeneity conduce to malware spread.
In this paper, the spreading behavior of malware across mobile devices is addressed. By introducing complex networks to model mobile networks, which follows the power-law degree distribution, a novel epidemic model for mobile malware propagation is proposed. The spreading threshold that guarantees the dynamics of the model is calculated. Theoretically, the asymptotic stability of the malware-free equilibrium is confirmed when the threshold is below the unity, and the global stability is further proved under some sufficient conditions. The influences of different model parameters as well as the network topology on malware propagation are also analyzed. Our theoretical studies and numerical simulations show that networks with higher heterogeneity conduce to the diffusion of malware, and complex networks with lower power-law exponents benefit malware spreading.</abstract><pub>Elsevier B.V</pub><doi>10.1016/j.cnsns.2016.01.019</doi><tpages>16</tpages></addata></record> |
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subjects | Asymptotic properties Complex network Computer simulation Malware Malware propagation Mathematical models Mobile network Network topology Networks Spreading Stability Thresholds |
title | Modeling the propagation of mobile malware on complex networks |
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