Evolutionary virus immune strategy for temporal networks based on community vitality

Abstract Preventing viruses spreading in networks is a hot topic. Existing immune strategies are mainly designed for static networks, which become ineffective for temporal networks. In this paper, we propose an evolutionary virus immune strategy for temporal networks, which takes into account the community evolution. First, we define a new metric, community vitality (CV) , to quantize the evolution characteristics of communities. Second, based on the community vitality, we propose an immune strategy which selects an optimized number of initial nodes according to node influence (NI) . Third, a theoretical analysis is proposed to measure the immune effect of the evolutionary immune strategy. Compared with the random immunization, the targeted immunization and the acquaintance immune strategy, we show that the proposed strategy has a much larger coverage, i.e., more nodes will have immune ability given the same number of initial immune nodes.

[1]  Zhen Jin,et al.  Epidemic spreading on complex networks with community structure , 2012, Appl. Math. Comput..

[2]  Albert-László Barabási,et al.  Understanding the Spreading Patterns of Mobile Phone Viruses , 2009, Science.

[3]  Sadie Creese,et al.  Virus Propagation in Heterogeneous Bluetooth Networks with Human Behaviors , 2012, IEEE Transactions on Dependable and Secure Computing.

[4]  Xiaohua Xia,et al.  When to initiate HIV therapy: a control theoretic approach , 2003, IEEE Transactions on Biomedical Engineering.

[5]  Yajin Zhou,et al.  Dissecting Android Malware: Characterization and Evolution , 2012, 2012 IEEE Symposium on Security and Privacy.

[6]  Cohen,et al.  Resilience of the internet to random breakdowns , 2000, Physical review letters.

[7]  Jun Zhang,et al.  Modeling and Analysis on the Propagation Dynamics of Modern Email Malware , 2014, IEEE Transactions on Dependable and Secure Computing.

[8]  Zonghua Liu,et al.  An alternative approach to characterize the topology of complex networks and its application in epidemic spreading , 2009, Frontiers of Computer Science in China.

[9]  Christos Faloutsos,et al.  Epidemic thresholds in real networks , 2008, TSEC.

[10]  Guofei Gu,et al.  A Large-Scale Empirical Study of Conficker , 2012, IEEE Transactions on Information Forensics and Security.

[11]  Hiroyuki Ohsaki,et al.  Community Structure and Interaction Locality in Social Networks , 2015, J. Inf. Process..

[12]  Junjie Wei,et al.  Global Hopf bifurcation and permanence of a delayed SEIRS epidemic model , 2016, Math. Comput. Simul..

[13]  Sancheng Peng,et al.  Smartphone Malware and Its Propagation Modeling: A Survey , 2014, IEEE Communications Surveys & Tutorials.

[14]  Min Li,et al.  Community Vitality in Dynamic Temporal Networks , 2013, Int. J. Distributed Sens. Networks.

[15]  Michalis Faloutsos,et al.  Epidemic Spread in Mobile Ad Hoc Networks: Determining the Tipping Point , 2011, Networking.

[16]  Hu Ke,et al.  Immunization for scale-free networks by random walker ∗ , 2006 .

[17]  Huaikou Miao,et al.  A Common Acquaintance Immunization Strategy for Complex Network , 2009, 2009 Eighth IEEE/ACIS International Conference on Computer and Information Science.

[18]  Azmi Jaafar,et al.  Symmetric Encryption Algorithm Inspired by Randomness and Non-Linearity of Immune Systems , 2012, Int. J. Nat. Comput. Res..

[19]  Shen Li,et al.  Virus propagation power of the dynamic network , 2013 .

[20]  Saswati Sarkar,et al.  Optimal Patching in Clustered Malware Epidemics , 2014, IEEE/ACM Transactions on Networking.

[21]  Shouhuai Xu,et al.  A Stochastic Model of Multivirus Dynamics , 2012, IEEE Transactions on Dependable and Secure Computing.

[22]  Jiming Liu,et al.  Modeling and Restraining Mobile Virus Propagation , 2013, IEEE Transactions on Mobile Computing.

[23]  Eitan Altman,et al.  Maximum Damage Malware Attack in Mobile Wireless Networks , 2010, 2010 Proceedings IEEE INFOCOM.

[24]  Ram Dantu,et al.  Fast Worm Containment Using Feedback Control , 2007, IEEE Transactions on Dependable and Secure Computing.

[25]  Donald F. Towsley,et al.  The effect of network topology on the spread of epidemics , 2005, Proceedings IEEE 24th Annual Joint Conference of the IEEE Computer and Communications Societies..

[26]  Leah B. Shaw,et al.  Effects of community structure on epidemic spread in an adaptive network , 2012, Physical review. E, Statistical, nonlinear, and soft matter physics.

[27]  Song Guo,et al.  Malware Propagation in Large-Scale Networks , 2015, IEEE Transactions on Knowledge and Data Engineering.

[28]  Hao Jiang,et al.  An environment aware epidemic spreading model and immune strategy in complex networks , 2015, Appl. Math. Comput..

[29]  Jeffrey O. Kephart,et al.  Directed-graph epidemiological models of computer viruses , 1991, Proceedings. 1991 IEEE Computer Society Symposium on Research in Security and Privacy.

[30]  Chung-Yuan Huang,et al.  A computer virus spreading model based on resource limitations and interaction costs , 2013, J. Syst. Softw..

[31]  Abdulrahman A. Mirza,et al.  Spammer Classification Using Ensemble Methods over Structural Social Network Features , 2014, 2014 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT).

[32]  Michalis Faloutsos,et al.  Threshold conditions for arbitrary cascade models on arbitrary networks , 2011, 2011 IEEE 11th International Conference on Data Mining.

[33]  Pan Hui,et al.  Optimal Distributed Malware Defense in Mobile Networks with Heterogeneous Devices , 2014, IEEE Transactions on Mobile Computing.

[34]  Nicola Santoro,et al.  Network Decontamination from a Black Virus , 2013, 2013 IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum.

[35]  Sujatha Kumari,et al.  Efficient Defence System For Avoid Malware Propagation In Mobile Network , 2015 .

[36]  Caterina M. Scoglio,et al.  Optimal Network-Based Intervention in the Presence of Undetectable Viruses , 2014, IEEE Communications Letters.

[37]  Guanhua Yan,et al.  Modeling Propagation Dynamics of Bluetooth Worms (Extended Version) , 2009, IEEE Transactions on Mobile Computing.

[38]  Somayeh Koohborfardhaghighi,et al.  One Node at One Step Discovery Process as an Immunization Strategy , 2014, J. Inf. Sci. Eng..

[39]  David Myers,et al.  Modified SIS epidemic model for analysis of virus spread in wireless sensor networks , 2013, Int. J. Wirel. Mob. Comput..

[40]  Johan van Leeuwaarden,et al.  Epidemic spreading on complex networks with community structures , 2016, Scientific Reports.

[41]  Cheng Wu,et al.  How Overlapping Community Structure Affects Epidemic Spreading in Complex Networks , 2014, 2014 IEEE 38th International Computer Software and Applications Conference Workshops.

[42]  Michalis Faloutsos,et al.  Virus Propagation on Time-Varying Networks: Theory and Immunization Algorithms , 2010, ECML/PKDD.

[43]  Sajal K. Das,et al.  This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. IEEE TRANSACTIONS ON MOBILE COMPUTING An Epidemic Theoretic Framework for Vulnerability Analysi , 2022 .