Improvement of Sybil Attack Detection in Vehicular Ad-Hoc Networks Using Cross-layer and Fuzzy Logic

Karimi, Mohamadreza; Sadeghi, Rasool

doi:10.52547/mjee.15.1.9

Document Type : Review Article

Authors

Mohamadreza Karimi ¹
Rasool Sadeghi ²

¹ Department of Computer Engineering, Dolatabad Branch, Islamic Azad University, Isfahan, Iran

² Department of Electrical Engineering, Dolatabad Branch, Islamic Azad University, Isfahan, Iran

https://doi.org/10.52547/mjee.15.1.9

Abstract

Nowadays Vehicular Ad-Hoc Networks (VANETs) are very popular and significantly used, due to their unique abilities to improve road safety. As a consequence, the security of these networks is of great importance and it has become one of the central topics in scientific and research fields such as information exchange. Sybil attack is one of the challenges for Ad-Hoc networks security. In this paper, a cross-layer approach and fuzzy logic method are used to detect the Sybil attacks. The proposed fuzzy logic method has four inputs form different OSI layers: entry time to the network, a number of neighbors, buffer size and signal to noise ratio. These inputs are imported to several membership functions of the fuzzy logic methods and the simulation results indicate that the proposed solution provides a robust technique in Sybil attack detection.

Keywords

20.1001.1.2345377.2021.15.1.2.1

References

[1] N. Patel, P. Modi, N. l Patel, and P. Modi, “Detecting Sybil attack using AODV in MANET,” Int. J. Adv. Eng. Res. Dev. Vol., vol. 1, no. 5, pp. 1–5, 2014.

[2] T. Krag and S. Büettrich, “Wireless mesh networking,” posted Wirel. DevCenter Jan, vol. 22, pp. 1–9, 2004.

[3] J.-P. Hubaux, J. Luo, and M. Raya, “The security of vehicular networks.,” in Workshop on Wireless Security, 2005, pp. 31–32.

[4] B. Parno and A. Perrig, “Challenges in securing vehicular networks,” in Workshop on hot topics in networks (HotNets-IV), 2005, no. 4, pp. 1–6.

[5] S. Marti, T. J. Giuli, K. Lai, and M. Baker, “Mitigating routing misbehavior in mobile ad hoc networks,” Proc. 6th Annu. Int. Conf. Mob. Comput. Netw. - MobiCom ’00, no. July, pp. 255–265, 2000.

[6] C.-Y. Tseng, P. Balasubramanyam, C. Ko, R. Limprasittiporn, J. Rowe, and K. Levitt, “A specification-based intrusion detection system for AODV,” Proc. 1st ACM Work. Secur. ad hoc Sens. networks - (SASN ’03), pp. 125–134, 2003.

[7] Y. Chin and H. Tseng, “Distributed Intrusion Detection Models for Mobile Ad Hoc Networks,” Ph.D. Thesis, pp. 1–133, 2006.

[8] F. Anjum and R. Talpade, “LiPaD: lightweight packet drop detection for ad hoc networks,” Veh. Technol. Conf. 2004. VTC2004-Fall. 2004 IEEE 60th, vol. 2, no. C, p. 1233–1237 Vol. 2, 2004.

[9] B. Sun, K. Wu, and U. W. Pooch, “Routing anomaly detection in mobile ad hoc networks,” in Computer Communications and Networks, 2003. ICCCN 2003. Proceedings. The 12th International Conference on, 2003, pp. 25–31.

[10] U. Khan, S. Agrawal, and S. Silakari, “Detection of Malicious Nodes (DMN) in vehicular ad-hoc networks,” Procedia Comput. Sci., vol. 46, no. Icict 2014, pp. 965–972, 2015.

[11] J. R. Douceur, “The sybil attack,” in International workshop on peer-to-peer systems, 2002, pp. 251–260.

[12] C. Piro, C. Shields, and B. N. Levine, “Detecting the sybil attack in mobile ad hoc networks,” in Securecomm and Workshops, 2006, 2006, pp. 1–11.

[13] J. Newsome, E. Shi, D. Song, and A. Perrig, “The sybil attack in sensor networks,” Proc. third Int. Symp. Inf. Process. Sens. networks - IPSN’04, p. 259, 2004.

[14] Q. Zhang, P. Wang, D. S. Reeves, and P. Ning, “Defending against Sybil Attacks in Sensor Networks,” 25th IEEE Int. Conf. Distrib. Comput. Syst. Work., no. October, pp. 185–191, 2005.

[15] Y. Zhang, W. Liu, W. Lou, Y. Fang, X. Ren, and H. Yu, “Location-based compromise-tolerant security mechanisms for wireless sensor networks,” IEEE J. Sel. areas Commun., vol. 24, no. 2, pp. 247–260, 2006.

[16] Y. Song, M. Demirbas, and Y. Song, “RSSI-based Scheme for Sybil Attack Detection in Wireless Sensor Networks,” Proc. 2006 Int. Symp. World Wireless, Mob. Multimed. Networks, pp. 564–570, 2006.

[17] D. Quercia and S. Hailes, “Sybil attacks against mobile users: Friends and foes to the rescue,” Proc. - IEEE INFOCOM, 2010.

[18] K. Rabieh, M. M. E. A. Mahmoud, T. N. Guo, and M. Younis, “Cross-layer scheme for detecting large-scale colluding Sybil attack in VANETs,” IEEE Int. Conf. Commun., vol. 2015–Septe, pp. 7298–7303, 2015.

[19] C. M. Chen, Y. L. Chen, and H. C. Lin, “An efficient network intrusion detection,” Comput. Commun., vol. 33, no. 4, pp. 477–484, 2010.

[20] D. M. da C. e Castro and M. Oliveira, “Thwarting the Sybil Attack in Wireless Ad Hoc Networks,” Gsd.Inesc-Id.Pt, pp. 1–28.

[21] D. Monica, “Thwarting the sybil attack in wireless ad hoc networks,” Inst. Super. Tec., 2009.

[22] P. Tyagi and D. Dembla, “Performance analysis and implementation of proposed mechanism for detection and prevention of security attacks in routing protocols of vehicular ad-hoc network (VANET),” Egypt. Informatics J., vol. 18, no. 2, pp. 133–139, 2017.

Majlesi Journal of Electrical Engineering

Improvement of Sybil Attack Detection in Vehicular Ad-Hoc Networks Using Cross-layer and Fuzzy Logic

References

References

Volume 15, Issue 1 - Serial Number 1
March 2021
Pages 9-18

Improvement of Sybil Attack Detection in Vehicular Ad-Hoc Networks Using Cross-layer and Fuzzy Logic

References

References

Volume 15, Issue 1 - Serial Number 1March 2021Pages 9-18

Volume 15, Issue 1 - Serial Number 1
March 2021
Pages 9-18