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Mutual Authentication Technique with Four Entities Implemented by Fuzzy Neural Network in 4-G Mobile Communications

Authors(3) :-Pijush Kanti Bhattacharjee, Sudipta Roy, Rajat Kumar Pal

4-G mobile communications system is offering high speed data communications technology having connectivity to all sorts of the networks including 2-G and 3-G mobile networks. Authentication of a mobile subscriber (MS) or a sub network and a main network are an important issue to check and minimize security threats or attacks. An advanced artificial intelligence based mutual authentication technique executed by fuzzy neural network with four entities is proposed. Voice frequency of the salutation or the selective words used by a subscriber like Hello, Good Morning, etc. is taken as first entity. Second entity is chosen as thumb fingerprint matching of the calling subscriber with his / her stored thumb fingerprint. Then third entity is taken as face image matching of the calling subscriber. Fourth entity is granted as probability of the salutation word from subscriber’s talking habit while initializing a call. These four entities such as probability of particular range of frequencies for the salutation word, the thumb fingerprint matching, the face image matching of the subscriber, using particular salutation or greeting word at the time of starting a call are used with most frequently, more frequently and less frequently by the calling subscriber like uncertainty in Artificial Intelligence. Now different relative grades are assigned to most frequently, more frequently and less frequently used parameters. Fuzzy operations such as intersection and union are computed taking three membership functions at a time out of four membership functions to adopt fuzzy neural network. Thereafter, the optimum or the final fuzzy operations are computed according to the assumed weightages. Lastly, the optimized fuzzy operations are defuzzified by the Composite Maxima method, and the results are tested according to the invented fuzzy neural rule. If the results are satisfactory, the subscriber or the sub network and the network (the switch or the server) are mutually authenticated in 4-G mobile communications.
Pijush Kanti Bhattacharjee, Sudipta Roy, Rajat Kumar Pal
Biometric scheme, Face image matching, Fuzzy neural network, Fuzzy operation, Identifier, Mutual authentication, Salutation word, Thumb fingerprint matching.
  1. J. Dunlop and D. G. Smith, Telecommunications Engineering, Chapman and Hall Publishers, U.K., Third Edition, 1994.
  2. T. S. Rappaport, Wireless Communication: Principles and Practice, Pearson Education, Second Edition, 2006.
  3. P. K. Bhattacharjee, “Telecommunications Revolution,” National Conference on Computer Science and Communication Technology (NCSCT-2007) at St. Joseph’s College, Tiruchirappalli, India, pp. 1-5, February 16-17, 2007.
  4. P. K. Bhattacharjee, “A New Era in Mobile Communications? GSM and CDMA,” National Conference on Wireless and Optical Communications (WOC-2007) at Punjab Engineering College (D.U.), India, pp. 118-126, December 13-14, 2007.
  5. W. C. Y. Lee, Wireless and Cellular Communications, 3rd Edition, McGraw Hill Publishers, 2008.
  6. C. Koner, P. K. Bhattacharjee, C. T. Bhunia, and U Maulik, “Mutual Authentication Technique Using Three Entities in 3-G Mobile Communications,” IEEE First Asian Himalayas International Conference on Internet (AH-ICI 2009), Kathmundu, Nepal, pp. 358-362, November 3-5, 2009.
  7. P. K. Bhattacharjee, C. Koner, C. T. Bhunia, and U Maulik, “Biometric Entity Based Mutual Authentication Technique for 3-G Mobile Communications,” International Journal of Computer Theory and Engineering, Singapore, vol. 2, no. 1, pp. 26-30, 2010.
  8. P. K. Bhattacharjee, C. Koner, C. T. Bhunia, and U Maulik, “Artificial Intelligence Based Authentication Technique with Three Entities in 3-G Mobile Communications,” International Journal of Computer and Electrical Engineering, Singapore, vol. 2, no. 2, pp. 339-344, 2010.
  9. P. K. Bhattacharjee, C. Koner, C. T. Bhunia, and U Maulik, “Artificial Intelligence Based Mutual Authentication Technique with Biometric Entities in 3-G Mobile Communications,” International Journal of Computer Theory and Engineering, Singapore, vol. 2, no. 2, pp. 205-210, 2010.
  10. Martin Sauter, Beyond 3G-Bringing Networks, Terminals and the Web Together, John Wiley & Sons Ltd. Publication, U. K., First Edition, 2009.
  11. M. L. Roberts, M. A. Temple, R. F. Mills, and R. A. Raines, “Evolution of the Air Interface of Cellular Communications Systems toward 4G Realization,” IEEE Communications Surveys and Tutorials, vol. 8, no. 1, pp. 2-23, Mar 2006.
  12. Vilem Novak, Jiri Mockor, Irina Perfilieva, Mathematical Principles of Fuzzy Logic, Kluwer Academic Publisher, 2006.
  13. J. Yan, M. Ryan, and J. Power, Using Fuzzy Logic: Towards Intelligent Systems, Prentice-Hall of India Pvt. Ltd., 1995.
  14. H. J. Zimmermann, Fuzzy Set Theory and Its Applications, Second Edition, Allied Publishers Ltd., New Delhi, 1996.
  15. Elaine Rich, Kevin Knight, Shivashankar B Nair, Artificial Intelligence, 3rd Edition, Tata McGraw Hill Education Pvt. Ltd., New Delhi, India, 2010.
  16. S. J. Russell and P. Norvig, Artificial Intelligence a Modern Approach, Pearson Education, Second Edition, 2003.
  17. P. K. Bhattacharjee and R. K. Pal, “A Novel Approach On Mutual Authentication Techniques In 4-G Mobile Communications,” International Journal of Computer Engineering and Computer Applications, California, USA, vol. 08, no. 01, pp. 42-49, July 2011.
  18. P. K. Bhattacharjee and R. K. Pal, “Mutual Authentication Technique Applying Three Entities in 4-G Mobile Communications,” International Journal of Computer Theory and Engineering, Singapore, vol. 3, no. 6, pp. 732-737, December 2011.
  19. P. K. Bhattacharjee and R. K. Pal, “Artificial Intelligence Based Authentication Technique Using Three Entities In 4-G Mobile Communications,” International Journal of Science and Technology, Assam University, Silchar, Assam, India, vol. 10, pp. 149-159, 2012.
  20. P. K. Bhattacharjee, S. Roy, and R. K. Pal, “Advance Artificial Intelligence Based Mutual Authentication Technique with Four Entities in 4-G Mobile Communication,” IEEE International Conference on Soft Computing and Machine Intelligence (ISCMI-2014) at New Delhi, India, pp. 139-145, September 26-27, 2014.
  21. P. K. Bhattacharjee, S. Roy, and R. K. Pal, “Mutual Authentication Technique with Four Entities Using Fuzzy Neural Network in 4-G Mobile Communications,” IETE sponsored National Conferences on Advances in Engineering, Technology and Management (AETM’15), M. M. University, Ambala, Haryana, India, pp. 69-76, April 4, 2015.
Publication Details
  Published in : Volume 1 | Issue 4 | September-October 2015
  Date of Publication : 2015-11-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 330-339
Manuscript Number : IJSRST15128
Publisher : Technoscience Academy
PRINT ISSN : 2395-6011
ONLINE ISSN : 2395-602X
Cite This Article :
Pijush Kanti Bhattacharjee, Sudipta Roy, Rajat Kumar Pal, "Mutual Authentication Technique with Four Entities Implemented by Fuzzy Neural Network in 4-G Mobile Communications", International Journal of Scientific Research in Science and Technology(IJSRST), Print ISSN : 2395-6011, Online ISSN : 2395-602X, Volume 1, Issue 4, pp.330-339, September-October-2015.
Journal URL : http://ijsrst.com/IJSRST15128

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