Notification: Our email services are now fully restored after a brief, temporary outage caused by a denial-of-service (DoS) attack. If you sent an email on Dec 6 and haven't received a response, please resend your email.
CFP last date
20 December 2024
Reseach Article

Malicious Objects Propagation Dynamics in the Network

Published on None 2011 by Dinesh Kumar Saini
Evolution in Networks and Computer Communications
Foundation of Computer Science USA
ENCC - Number 1
None 2011
Authors: Dinesh Kumar Saini
5013fd0b-63b6-4e0e-8ba7-52c42b509fee

Dinesh Kumar Saini . Malicious Objects Propagation Dynamics in the Network. Evolution in Networks and Computer Communications. ENCC, 1 (None 2011), 44-51.

@article{
author = { Dinesh Kumar Saini },
title = { Malicious Objects Propagation Dynamics in the Network },
journal = { Evolution in Networks and Computer Communications },
issue_date = { None 2011 },
volume = { ENCC },
number = { 1 },
month = { None },
year = { 2011 },
issn = 0975-8887,
pages = { 44-51 },
numpages = 8,
url = { /specialissues/encc/number1/3719-encc008/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Special Issue Article
%1 Evolution in Networks and Computer Communications
%A Dinesh Kumar Saini
%T Malicious Objects Propagation Dynamics in the Network
%J Evolution in Networks and Computer Communications
%@ 0975-8887
%V ENCC
%N 1
%P 44-51
%D 2011
%I International Journal of Computer Applications
Abstract

The network world is enormous, dynamic, divers and incredibly very high complex. Survival of computer network is highly depended on the capability of the network to fight with malicious objects which are abundantly available in the cyber space. Our network world is growing larger in size and ways of networking like wired and wireless with different techniques are also growing, but reliability and robustness is the issue of concern in the today’s network. In this paper biologically based mathematical inspired modelling is carried out to monitor the spread of these malicious objects in the network. An attempt is made to develop a discrete-time “Susceptible -Attacked-Infectious-Non-Infectious (SAIN)” model for computer infection with the aim of estimating parameters such as time of attack, incubation time, and mean infection time by using probabilistic approach. SAIN model is basically compartment-specific approach; each compartment is having distinct boundaries. Computer nodes transfers from one compartment to other such as Susceptible to Attacked, Attacked to Infectious, and Infectious to Non-Infectious with some stochastic random variable. In the end of the paper it is described where and how to use this mathematical modelling for designing the cyber defence systems.

References
  1. Housholder et al. (2002). Computer Attack Trends Challenge Internet Security, Security and Privacy (supplement to Computer), Vol. 35, No. 4, 5-7.
  2. Chi, S.D., Park, J.S., Jung, K.C., Lee J.S. (2001). Network Security Modeling and Cyber Attack Simulation Methodology, LNCS, Vol. 2119.
  3. Bimal Kumar Mishra and Dinesh Kumar Saini “Mathematical Models on Computer viruses” Journal of Applied Mathematics and Computation, Volume 187, Issue 2, 15 April 2007, Pages 929-936.
  4. Bimal Kumar Mishra and Dinesh Kumar Saini “SEIRS epidemic model of transmission of malicious objects in computer network” Elsevier International Journal of Applied Mathematics and Computation, Volume 188, Issue 2, 15 May 2007, Pages 1476-1482.
  5. Dinesh Kumar Saini and Hemraj Saini "VAIN: A Stochastic Model for Dynamics of Malicious Objects", the ICFAI Journal of Systems Management, Vol.6, No1, pp. 14- 28, February 2008.
  6. Hemraj Saini and Dinesh Kumar Saini "Malicious Object dynamics in the presence of Anti Malicious Software” European Journal of Scientific Research ISSN 1450-216X Vol.18 No.3 (2007), pp.491-499 © Euro Journals Publishing, Inc. 2007 http://www.eurojournals.com/ejsr.htm
  7. Dinesh Kumar Saini and Hemraj Saini “Proactive Cyber Defense and Reconfigurable Framework for Cyber Security” International Review on computer and Software (IRCOS) Vol.2. No.2. March 2007, pages 89-98.
  8. Moore, D., Paxson, V., Savage, S., Shannon, C., Staniford, S., Weaver, N. (2003). Inside the Slammer Worm, IEEE Security and Privacy, Vol. 01, No. 4, 33-39.
  9. Chen, Z., Gao, L., Kevin, Kwiat (2003). Modeling the Spread of Active Worms, In Proceedings of IEEE INFOCOMM, Vol. 3, 1890-1900.
  10. Shannon, C., Moore, D. (2004). The Spread of the Witty Worm, IEEE Security and Privacy Magazine, Vol. 2, No. 4, 46-50.
  11. Zou, C., Gong, W., Towsley, D. (2002). Code Red Worm Propagation Modeling and Analysis, In Proceedings of ACM Conference on Computer and Communication Security (CCS), 138-147.
  12. Dym C.L. Principles of mathematical modeling. 2nd Ed., Elsevier-Academic press: California; 2004.
  13. Sayadjari O.S. Cyber Defense: art to science. Communication of the ACM. 2004, Volume-47, Issue-3, ACM Press New York, NY, USA, pp. 52-57.
  14. Ning P., Xu D. Learning attack strategies from intrusion alerts. Proceedings of the 10th ACM conference on computer and communications security. ACM Press New York NY, USA. pp. 200-209; 2003.
  15. Ning P., Cui Y., Reeves D. S. Constructing attack scenarios through correlation of intrusion alerts. Proceedings of the 9th ACM Conf. on Computer and Communications Security. ACM Press New York NY, USA. pp. 245-254; 2002.
  16. Ning P., Cui Y., Reeves D. S, Xu D. Techniques and tools for analyzing instruction alerts. ACM Transactions on Information and System Security (TISSEC). 2004, Volume-7, Issue-2, ACM Press New York NY, USA, pp. 274-318.
  17. Weaver N., Kesidis G., Paxson V. Preliminary Results Using Scale down to Explore Worm Dynamics. Proceedings of the 2004 ACM workshop on Rapid malcode table of contents. ACM Press New York NY, USA. pp. 65-72; 2004.
  18. Porras P., Briesemeister L., Skinner K., Levitt K., Rowe J., Ting Y. A. A Hybrid Quarantine Defense. Proceedings of the 2004 ACM workshop on Rapid malcode table of contents. ACM Press New York NY, USA. pp. 73-82; 2004.
  19. Gupta A., DuVarney D. C. Using Predators to Combat Worms and Viruses: A Simulation-Based Study. 20th Annual Computer Security Applications Conference. IEEE Computer Society Washington, DC, USA. pp. 116-125; 2004.
  20. Liljenstam M., Nicol D. M., Berk V. H., Gray R. S. Simulating Realistic Network Worm Traffic for Worm Warning System Design and Testing. Proceedings of the 2003 ACM workshop on Rapid malcode table of contents. ACM Press New York NY, USA. pp. 24-33; 2003.
  21. Jiang X., Xu D., Lei S., Ruth P., Sun J. Worm Meets Beehive. Technical Report CSD TR 04-027, Purdue University, Department of Computer Sciences, May 2004.
  22. Nicol D. M., Liljenstam M., Liu J. Multiscale Modeling and Simulation of Worm Effects on the Internet Routing Infrastructure. Proceedings of 13th International Conference on Modeling Techniques and Tools for Computer Performance Evaluation (Performance TOOLS 2003), Urbana, IL, Sept 2003.
  23. Briesemeister L., Porras P. Microscopic Simulation of a Group Defense Strategy. Proceedings of the 19th Workshop on Principles of Advanced and Distributed Simulation table of contents. ACM Press New York NY, USA. pp. 254-261; 2005.
  24. Cai M., Hwang K., Kwok Y.K., Song S., Chen Y. Collaborative Internet Worm Containment. IEEE ecurity and Privacy. 2005, Volume-03, Issue-3, IEEE Computer Society Washington, DC, USA, pp. 25-33.
  25. Douceur J.R. The Sybil attack. In Proceedings of Workshop on Peer-to-Peer Systems (IPTPS). Editors: P. Druschel, F. Kaashoek, A. Rowstron (Eds.). Springer-Verlag GmbH. 2002, Volume 2429 / 2002, pp. 251 - 260.
  26. Eschenauer, Gligor V. A key-management scheme for distributed sensor networks. In Proceedings of the 9th ACM Conference on Computer and Communication Security (CCS). ACM Press New York, NY, USA. pp. 41-47; 2002.
  27. Dinesh Kumar Saini “A Mathematical Model for the Effect of Malicious Object on Computer Network Immune System” Applied Mathematical Modeling, 35(2011) Page No. 3777-3787 USA, doi:10.1016/.2011.02.025.
  28. Dinesh Kumar Saini, Jabar H. Yousif, and Wail M. Omar “Enhanced Inquiry Method for Malicious Object Identification” ACM SIGSOFT Volume 34 Number 3 May 2009, ISSN: 0163-5948, USA
  29. Dinesh Kumar Saini, Imran Azad, Nitin B Raut, and Lingaraj A. Hadimani, “Utility Implementation for Cyber Risk Insurance Modeling” The 2011 International Conference of Information Engineering, (ICFE-2011) World Congress in Engineering, July 6-9th London UK.
Index Terms

Computer Science
Information Sciences

Keywords

Malicious Object propagation Mathematical Modelling