Advertisement

Wireless Networks

, Volume 25, Issue 7, pp 4115–4132 | Cite as

MLAMAN: a novel multi-level authentication model and protocol for preventing wormhole attack in mobile ad hoc network

  • Tu T. Vo
  • Ngoc T. LuongEmail author
  • Doan Hoang
Article

Abstract

Wormhole attack is a serious security issue in Mobile Ad hoc Network where malicious nodes may distort the network topology and obtain valuable information. Many solutions, based on round trip time, packet traversal time, or hop-count, have been proposed to detect wormholes. However, these solutions were only partially successful in dealing with node high-speed mobility, variable tunnel lengths, and fake information by malicious nodes. To address those issues, this paper proposes a novel multi-level authentication model and protocol (MLAMAN) for detecting and preventing wormhole attacks reliably. MLAMAN allows all intermediate nodes to authenticate control packets on a hop-by-hop basis and at three levels: (1) the packet level where the integrity of the packets can be verified, (2) the node membership level where a public key holder-member can be certified, and (3) the neighborhood level where the neighborhood relationship between nodes can be determined. The novelty of the model is that it prevents malicious nodes from joining the network under false information and pretense. It detects wormhole nodes effectively under various scenarios including variable tunnel lengths and speeds of moving nodes. The effectiveness of our approach is confirmed by simulation results through various scenarios.

Keywords

MLA MLAMAN Mobile ad hoc network Multi-level authentication Network security 

References

  1. 1.
    Akilarasu, G., & Shalinie, S. M. (2017). Wormhole-free routing and DoS attack defense in wireless mesh networks. Wireless Networks, 23(6), 1709–1718.Google Scholar
  2. 2.
    Chiu, H., & Wong Lui, K. (2006). DelPHI: Wormhole detection mechanism for Ad hoc Wireless Networks. In International symposium on wireless pervasive computing proceedings (pp. 6–11).Google Scholar
  3. 3.
    DARPA. (2005). The network simulator NS2. http://www.isi.edu/nsnam/ns/.
  4. 4.
    Diffie, W., & Hellman, M. E. (1976). New directions in cryptography. IEEE Transactions on Information Theory, 22, 644–654.MathSciNetzbMATHGoogle Scholar
  5. 5.
    Eiman, A., & Biswanath, M. (2012). A survey on routing algorithms for wireless ad-hoc and mesh networks. Computer Networks, 56(2), 940–965.Google Scholar
  6. 6.
    Gurung, S., & Chauhan, S. (2017). A novel approach for mitigating route request flooding attack in MANET. Wireless Networks.  https://doi.org/10.1007/s11276-017-1515-0.Google Scholar
  7. 7.
    Gurung, S., & Chauhan, S. (2018). A novel approach for mitigating gray hole attack in MANET. Wireless Networks, 24(2), 565–579.Google Scholar
  8. 8.
    Hu, Y. C., Perrig, A., & Johnson, D. B. (2003). Packet leashes: A defense against wormhole attacks in wireless networks. Twenty-second Annual Joint Conference of the IEEE computer and communications societies, 3, 1976–1986.Google Scholar
  9. 9.
    Imrich, C., Marco, C., & Jennifer, J. (2003). Mobile ad hoc networking: Imperatives and challenges. Ad Hoc Networks, 1(1), 13–64.Google Scholar
  10. 10.
    Jan, V. M., Ian, W., & Winston, K. S. (2012). Security threats and solutions in MANETs: A case study using AODV and SAODV. Journal of Network and Computer Applications, 35(4), 1249–1259.Google Scholar
  11. 11.
    Jen, S. M., Laih, C. S., & Kuo, W. C. (2009). A hop-count analysis scheme for avoiding wormhole attacks in MANET. Sensors, 9(6), 5022–5039.Google Scholar
  12. 12.
    Johnson, D. B., & Maltz, D. A. (1996). Dynamic source routing in ad hoc wireless networks (pp. 153–181). Boston: Springer.Google Scholar
  13. 13.
    Jones, P. (2001). US secure hash algorithm 1 (SHA1). https://tools.ietf.org/html/rfc3174.
  14. 14.
    Karlsson, J., Dooley, L. S., & Pulkkis, G. (2011). A New MANET wormhole detection algorithm based on traversal time and hop count analysis. Sensors, 11(12), 11,122–11,140.Google Scholar
  15. 15.
    Karlsson, J., Dooley, L. S., & Pulkkis, G. (2013). Identifying time measurement tampering in the traversal time and hop count analysis (TTHCA) wormhole detection algorithm. Sensors, 13(5), 6651–6668.Google Scholar
  16. 16.
    Khurana, S., & Gupta, N. (2011). End-to-end protocol to secure ad hoc networks against wormhole attacks. Security and Communication Networks, 4(9), 994–1002.Google Scholar
  17. 17.
    Lazos, L., & Poovendran, R. (2004). SeRLoc: Secure range-independent localization for wireless sensor networks. In Proceedings of the 3rd ACM Workshop on Wireless Security (pp. 21–30).Google Scholar
  18. 18.
    Lazos, L., Poovendran, R., Meadows, C., Syverson, P., & Chang, L.W. (2005). Preventing wormhole attacks on Wireless Ad hoc Networks: A graph theoretic approach. In IEEE Wireless Communications and Networking Conference (Vol. 2, pp. 1193–1199)Google Scholar
  19. 19.
    Manel, G. Z. (2002). Secure ad hoc on-demand distance vector routing. ACM SIGMOBILE Mobile Computing and Communications Review, 6(3), 106–107.Google Scholar
  20. 20.
    Nagrath, P., Aneja, S., Gupta, N., & Madria, S. (2016). Protocols for mitigating blackhole attacks in delay tolerant networks. Wireless Networks, 22(1), 235–246.Google Scholar
  21. 21.
    Ngai, E. C., Liu, J., & Lyu, M. R. (2007). An efficient intruder detection algorithm against sinkhole attacks in wireless sensor networks. Computer Communications, 30(11), 2353–2364.Google Scholar
  22. 22.
    Ngoc, L. T., & Tu, V. T. (2017). Whirlwind: A new method to attack routing protocol in mobile ad hoc network. International Journal of Network Security, 19(5), 832–838.Google Scholar
  23. 23.
    Perkins, C. E., & Royer, E. M. (1999). Ad-hoc on-demand distance vector routing. In Proceedings of the Second IEEE Workshop on Mobile Computer Systems and Applications (pp. 90–100).Google Scholar
  24. 24.
    Pietro, R. D., Guarino, S., Verde, N., & Domingo-Ferrer, J. (2014). Security in wireless ad-hoc networks—A survey. Computer Communications, 51, 1–20.Google Scholar
  25. 25.
    Poovendran, R., & Lazos, L. (2007). A graph theoretic framework for preventing the wormhole attack in wireless ad hoc networks. Wireless Networks, 13(1), 27–59.Google Scholar
  26. 26.
    Sanzgiri, K., Dahill, B., Levine, B.N., Shields, C., & Belding-Royer, E.M. (2002). A secure routing protocol for Ad hoc Networks. In Proceedings on 10th IEEE International Conference on Network Protocols, 2002 (pp. 78 – 87).Google Scholar
  27. 27.
    Shahabi, S., Ghazvini, M., & Bakhtiarian, M. (2016). A modified algorithm to improve security and performance of AODV protocol against black hole attack. Wireless Networks, 22(5), 1505–1511.Google Scholar
  28. 28.
    TLS-Library. (2017). RSA source code. https://tls.mbed.org/rsa-source-code.
  29. 29.
    Yoon, J., Liu, M., & Noble, B. (2003). Random waypoint considered harmful. In IEEE INFOCOM 2003. Twenty-second Annual Joint Conference of the IEEE Computer and Communications Societies (IEEE Cat. No.03CH37428) (Vol. 2, pp. 1312–1321).Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Faculty of Information TechnologyHue University of Sciences, Hue UniversityHueViet Nam
  2. 2.Faculty of Mathematics and Informatics Teacher EducationDong Thap UniversityCao Lanh CityViet Nam
  3. 3.Faculty of Engineering and Information TechnologyThe University of Technology SydneySydneyAustralia

Personalised recommendations