International E-publication: Publish Projects, Dissertation, Theses, Books, Souvenir, Conference Proceeding with ISBN.  International E-Bulletin: Information/News regarding: Academics and Research

A Method in Security of Wireless Sensor Network based on Optimized Artificial immune system in Multi-Agent Environments

Author Affiliations

  • 1Department of Computer Science, Tabarestan University of Chalous, IRAN
  • 2School of Engineering and Technology, Asia Pacific University of Technology and Innovation, MALAYSIA
  • 3Institute of Bioscience, University Putra Malaysia, MALAYSIA
  • 4Faculty of Computer system and Information Technology, University Of Malaya, MALAYSIA

Res. J. Recent Sci., Volume 2, Issue (10), Pages 99-106, October,2 (2013)

Abstract

Security in computer networks is one of the most interesting aspects of computer systems. It is typically represented by theinitials CIA: confidentiality, integrity, and authentication or availability. Although, many access levels for data protectionhave been identified in computer networks, the intruders would still find lots of ways to harm sites and systems. Theaccommodation proceedings and the security supervision in the network systems, especially wireless sensor networks havebeen changed into a challenging point. One of the newest security algorithms for wireless sensor networks is ArtificialImmune System (AIS) algorithm. Human lymphocytes play the main role in recognizing and destroying the unknownelements. In this article, we focus on the inspiration of these defective systems to guarantee the complications security usingtwo algorithms; the first algorithms proposed to distinguish self-nodes from non-self ones by the related factors and thesecond one is to eliminate the enemy node danger.The results showed a high rate success and good rate of detecting forunknown object; it could present the best nodes with high affinity and fitness to be selected to confront the unknown agents.

References

  1. Azgomi MA, Khalili A., Proceedings of the First Workshopon Formal Methods for Wireless Systems, Electronic Notesin Theoretical Computer Science., 242(2), 31–42 (2009)
  2. Fesharaki M., Alipour G.H. and Rashidi A.J., Sensorintelligent selection service in the battlefield based ongenetic algorithms and neural networks”, 3rd Conference ofIran's Scientific Society of Command, Control,Communications, Computers and Intelligences (2009)
  3. Greensmith J., New Frontiers For An Artificial ImmuneSystem', Master’s Thesis, supervised by Dr. Steve Cayzerand Dr. Jason Noble, University of Leeds and HewlettPackard Labs, Bristol (2003)
  4. Dasgupta D., Artificial Neural Networks and ArtificialImmune Systems: Similarities and Differences,IEEEInternational Conference on Systems, Man andCybernetics, Orlando, Florida, 1(12), 873-878 (1997)
  5. Zheng J., Chen Y. and Zhang W., A Survey of artificialimmune applications, Artificial Intelligence Revie.,34(1), 19-34 (2010)
  6. Watkins A. and Timmis J., Exploiting Parallelism Inherentin AIRS, an Artificial Immune Classifier, In Proceedings ofthe 3rd International Conference on Artificial ImmuneSystems (ICARIS2004) held in Catania, Italy, LectureNotes in Computer Science (LNCS), 3239 (2004)
  7. Aickelin and Dipankar Dasgupta, Chapter 13: ArtificialImmune Systems” MATHEMATICS AND STATISTICS,Search Methodologies, 1st ed. Corr. 2nd printing, VI, 620p. 99 illus., Springer (2005)
  8. Dasgupta D., Gonzalez F., Vemuri Ed V.R., ArtificiaImmune Systems in Intrusion Detection, from the book,Enhancing Computer Security with Smart Technology,165-208 (2005)
  9. Ramakrishnan S. and Srinivasan S.,Intelligent agent basedartificial immune system for computer security--a review,32(1-4),13-43 (2009)
  10. Dasgupta D., Immunity-Based Intrusion Detection Systems:A General Framework, Twenty-second NationalInformation Systems Security Conference (NISSC), 147-160 (1999)
  11. Katenka N., Levina E. and Michailidis G., TrackingMultiple Targets Using Binary Decisions from WirelessSensor Networks, American Statistical Association, (2009)
  12. Javadzadeh R. and Meybodi M.R., Memetic ArtificialImmune Systems., Proceedings of The Third JointCongress on Fuzzy and Intelligent Systems, University ofYazd, Yazd, Iran (2009)