Detaining and avoiding mobile virus propagation by considering human behavior


  • C M Anagha PG Scholar, Hindusthan Institute of Technology, Coimbatore
  • Uma S Professor and Head, Hindusthan Institute of Technology, Coimbatore
  • Kumar MM Asst. Professor, Dept. of PG-CSE Hindusthan Institute of Technology, Coimbatore


Mobile networks, phone virus, human mobility, autonomy-oriented computing, Danger Theory, preimmunization, adaptive Dissemination


Malware, short for malicious software, is software used to disrupt computer operation, gather sensitive information, or gain access to private computer systems. Malware is designed to cause damage to a standalone computer or a networked pc. So wherever a malware term is used it means a program which is designed to damage your computer it may be a virus, worm. So, in order to overcome this problem we propose a two-layer network model for simulating virus propagation through both Bluetooth and SMS. We examine two strategies for restraining mobile virus propagation, i.e., preimmunization and adaptive dissemination strategies drawing on the methodology of autonomy-oriented computing (AOC). This method can effectively restrain virus propagation in a large-scale, dynamically evolving, and/or community based network. In order to increase the effectiveness of inhibiting the propagation of mobile phone viruses, we introduce an innovative approach called a virus detection model based on the Danger Theory. This model includes four phases: danger capture, antigen presentation, antibody generation and antibody distribution. Due to the distributed and cooperative mechanism of artificial immune system, the proposed model lowers the storage and computing consumption of mobile phones. By using this system, we can effectively inhibit and delete the virus files.


. Chao Gao and Jiming Liu, “Modeling and Restraining Mobile Virus Propagation,” Ieee Transactions On Mobile Computing, Vol. 12, No. 3, March 2013. (Base paper)

. Cheng .J, S.H.Y. Wong, H. Yang, and S. Lu, “Smartsiren Virus Detection and Alert for Smartphones,” Proc. Fifth Int’l Conf. Mobile Systems, Applications, and Services (MobiSys ’07), pp. 258-271, 2007.

. De .P, Y. Liu, and S.K. Das, “An Epidemic Theoretic Framework for Vulnerability Analysis of Broadcast Protocols in Wireless Sensor Networks,” IEEE Trans. Mobile Computing, vol. 8, no. 3, pp. 413-425, Mar. 2009.

. Lee .K, S. Hong, S.J. Kim, I. Rhee, and S.Chong, “SLAW: A Mobility Model for Human Walks,” Proc. IEEE INFOCOM, pp. 855-863, 2009.

. Mei .A and J. Stefa, “SWIM: A Simple Model to Generate Small Mobile Worlds,”Proc. IEEE INFOCOM, pp. 2106-2113, 2010.

. Ruitenbeek .E.V and F. Stevens, “Quantifying the Effectiveness of Mobile Phone Virus Response Mechanisms,” Proc. 37th Ann. IEEE/ IFIP Int’l Conf. Dependable Systems and Networks (DSN’07), pp. 790-800, 2007.

. Xie .L, X. Zhang, A. Chaugule, T. Jaeger, and S. Zhu, “Designing System-Level Defenses against Cellphone Malware,” Proc. IEEE 28th Int’l Symp. Reliable Distributed Systems (SRDS ’09), pp. 83-90, 2009.

. Zhu .Z, G. Cao, S. Zhu, S. Ranjan, and A. Nucci, “A Social Network Based Patching Scheme for Worm Containment in Cellular Networks,” Proc. IEEE INFOCOM, pp. 1476-1484, 2009.

. Zou .C.C, D. Towsley, and W. Gong, “Modeling and Simulation Study of the Propagation and Defense of Internet E-Mail Worms,” IEEE Trans. Dependable and Secure Computing, vol. 4, no. 2, pp. 105-118, Apr.-June 2007.

. Zyba .G, G.M. Voelker, M. Liljenstam, A.Mehes, and P. Johansson, “Defending Mobile Phones from Proximity Malware,”Proc. IEEE INFOCOM, pp. 1503-1511, 2009.




How to Cite

C M, A., Uma, S., & Kumar, M. M. (2024). Detaining and avoiding mobile virus propagation by considering human behavior. COMPUSOFT: An International Journal of Advanced Computer Technology, 3(03), 619–623. Retrieved from



Original Research Article

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