IJRCS – Volume 5 Issue 3 Paper 6

EFFICIENT AND DYNAMIC GROUPING SCHEME WITH SECURE AUTHENTICATION FOR VANET

Author’s Name : Gisna Baby | Ms R Sujitha

Volume 05 Issue 03  Year 2018  ISSN No:  2349-3828  Page no:  29-37

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Abstract:

Data congestion control is an efficient way to decrease packet loss and delay and increase the reliability of VANETs. In this paper, a centralized and localized data congestion control strategy is proposed to control data congestion using roadside units (RSUs) at intersections.The proposed strategy consists of three units for detecting congestion, clustering messages, and controlling data congestion. In this strategy, the channel usage level is measured to detect data congestion in the channels. The messages are gathered, filtered, and then clustered by machine learning algorithms. K- means algorithm clusters the messages based on message size, validity of messages, and type of messages. The data congestion control unit determines appropriate values of transmission range and rate, contention window size, and arbitration inter frame spacing for each cluster.

Keywords:

Data Compression, Privacy, Protocol Design, Security, Vehicular Ad Hoc Networks (VANETs)

References:

  1. IEEE Std.1609.2-2013. [Online]. Available: https://standards.ieee.org/findstds/ standard/1609.2-2013.html
  2. “Legislative resolution on the proposal for a directive of the European parliament and of the council on the retention of data processed in connection with the provision of public electronic communication services and amending directive 2002/58/EC,” Eur. Parliament, Brussels, Belgium, (COM(2005)0438 C6-0293/2005 2005/0182(COD)), 2005.
  3. V. Daza, J. Domingo-Ferrer, F. Sebé, and A. Viejo, “Trustworthy privacy preserving car-generated announcements in vehicular ad hoc networks,” IEEE Trans. Veh. Technol., vol. 58, no. 4, pp. 1876–1886, May 2009.
  4. F. Qu, Z. Wu, F. Wang, and W. Cho, “A security and privacy review of VANETs,” IEEE Trans. Intell. Transp. Syst., vol. 16, no. 6, pp. 2958– 2996, Dec. 2015.
  5. X. Wen, L. Shao, Y. Xue, and W. Fang, “A rapid learning algorithm for vehicle classification,” Inf. Sci., vol. 295, no. 2015, pp. 395–406, 2015.
  6. M. Raya and J. Hubaux, “The security of vehicular ad hoc networks,” in Proc. SASN, 2005, pp. 11–21.
  7. M. Raya and J. Hubaux, “Securing vehicular ad hoc networks,” J. Comput. Security, vol. 15, no. 1, pp. 39–68, 2007.
  8. X. Lin, X. Sun, P.-H. Ho, and X. Shen, “GSIS: A secure and privacy preserving protocol for vehicular communications,” IEEE Trans. Veh. Technol., vol. 56, no. 6, pp. 3442–3456, 2007.
  9. Q. Wu, J. Domingo-Ferrer, and U. González-Nicolás, “Balanced trustworthiness, safety, and privacy in vehicle-to-vehicle communications,” IEEE Trans. Veh. Technol., vol. 59, no. 2, pp. 559–573, Feb. 2010.
  10. L. Zhang, Q. Wu, A. Solanas, and J. Domingo-Ferrer, “A scalable robust authentication protocol for secure vehicular communications,” IEEE Trans. Veh. Technol., vol. 59, no. 4, pp. 1606–1617, May 2010.
  11. X. Zhu, S. Jiang, L. Wang, and H. Li, “Efficient privacy-preserving authentication for vehicular ad hoc networks,” IEEE Trans. Veh. Technol., vol. 63, no. 2, pp. 907–919, Feb. 2014.
  12. L. Zhang, Q. Wu, B. Qin, J. Domingo-Ferrer, and B. Liu, “Practical secure and privacy-preserving scheme for value-added applications in VANETs,” Comput. Commun., vol. 71, no. 2015, pp. 50–60, Nov. 2015.
  13. J. Li, H. Lu, and M. Guizani, “ACPN: A novel authentication framework with conditional privacy-preservation and non-repudiation for VANETs,” IEEE Trans. Parallel Distrib. Syst., vol. 26, no. 4, pp. 938– 948, Apr. 2015.
  14. L. Zhang, C. Hu, Q. Wu, J. Domingo-Ferrer, and B. Qin, “Privacy preserving vehicular communication authentication with hierarchical aggregation and fast response,” IEEE Trans. Comput., to be published, doi: 10.1109/TC.2015.2485225.
  15. C. Zhang, R. Lu, X. Lin, P.-H. Ho, and X. Shen, “An efficient identity based batch verification scheme for vehicular sensor networks,” in Proc. IEEE INFOCOM, 2008, pp. 246–250.
  16. E. Kiltz and K. Pietrzak, “Leakage resilient ElGamal encryption,” in Proc. ASIACRYPT, 2010, pp. 595–612.
  17. L. Zhang, Q. Wu, B. Qin, and J. Domingo-Ferrer, “APPA: Aggregate privacy-preserving authentication in vehicular ad hoc networks,” inProc. ISC, 2011, pp. 293–308.
  18. P. Golle, D. Greene, and J. Staddon, “Detecting and correcting malicious data in VANETs,” in Proc. VANET, 2004, pp. 29–37.
  19. C. Laurendeau and M. Barbeau, “Probabilistic localization and tracking of malicious insiders using hyperbolic position bounding in vehicular networks,” EURASIP J. Wireless Commun. Netw., vol. 2, pp. 1–13, 2009.
  20. B. Parno and A. Perrig, “Challenges in securing vehicular networks,” in Proc. HotNets-IV, 2005, pp. 1–6.