Wireless Networks

, Volume 25, Issue 4, pp 1731–1747 | Cite as

SRDPV: secure route discovery and privacy-preserving verification in MANETs

  • Teng LiEmail author
  • JianFeng Ma
  • Cong Sun


In the routing discovery phase of the Mobile Ad hoc Networks (MANETs), the source node tries to find a fast and secure path to transmit data. However, the adversaries attempt to get the rights of routing during this phase ,then the networks can easily be paralyzed during the data transmission phase. During the routing discovery phase, finding a good path is already a challenge and verifying the security of the established path without revealing any privacy of the nodes adds a new dimension to the problem. In this paper, we present SRDPV, an approach that helps the source find the benign destination dynamically and conducts privacy-preserving verification of the path. Our approach first finds the benign destination. Then, it spreads the verification tasks across multiple nodes and verifies the log entries without revealing private data of the nodes. Unlike the traditional debugging system to detect the faults or misbehaviors of the nodes after the attacks, SRDPV can guarantee the source to avoid transmitting data through malicious nodes at the beginning and perform the verification without introducing a third party. We demonstrate the effectiveness of the approach by applying SRDPV in two scenarios: resisting the collaborative black-hole attack of the AODV protocol and detecting injected malicious intermediated routers which commit active and passive attacks in MANETs. We compared our approach with the existing secure routing algorithms and the results show that our approach can detect the malicious nodes, and the overhead of SRDPV is moderate.


MANETs Routing Reasoning Verification Privacy 



This work is supported by the National High Technology Research and Development Program (863 Program) of China (No. 2015AA017203), the National Natural Science Foundation of China (Nos. 61303033, 61502- 368, 61602537), the Key Program of NSFC (No. U14052- 55), the Natural Science Basis Research Plan in Shaanxi Province of China (No. 2016JM6034), China 111 Project (No. B16037), and the Special Research Foundation of MIIT (No. MJ-2014-S-37).


  1. 1.
    Abusalah, L., Khokhar, A., & Guizani, M. (2008). A survey of secure mobile ad hoc routing protocols. Communications Surveys & Tutorials, IEEE, 10(4), 78–93.CrossRefGoogle Scholar
  2. 2.
    Sahingoz, O. K. (2014). Networking models in flying ad-hoc networks (fanets): Concepts and challenges. Journal of Intelligent & Robotic Systems, 74(1–2), 513.CrossRefGoogle Scholar
  3. 3.
    Li, Z., & Wu, Y. (2017). Smooth mobility and link reliability-based optimized link state routing scheme for manets. IEEE Communications Letters, 21(7), 1529–1532. Scholar
  4. 4.
    Perkins, C., Belding-Royer, E., & Das, S. (2003). Ad hoc on-demand distance vector (AODV) routing, Technical report.Google Scholar
  5. 5.
    Chatterjee, S., & Das, S. (2015). Ant colony optimization based enhanced dynamic source routing algorithm for mobile ad-hoc network. Information Sciences, 295, 67–90.MathSciNetCrossRefGoogle Scholar
  6. 6.
    Deng, H., Li, W., & Agrawal, D. P. (2002). Routing security in wireless ad hoc networks. IEEE Communications Magazine, 40(10), 70–75.CrossRefGoogle Scholar
  7. 7.
    Hayajneh, T., Krishnamurthy, P., Tipper, D., & Le, A. (2012). Secure neighborhood creation in wireless ad hoc networks using hop count discrepancies. Mobile Networks and Applications, 17(3), 415–430.CrossRefGoogle Scholar
  8. 8.
    Hayajneh, T., Doomun, R., Al-Mashaqbeh, G., & Mohd, B. J. (2014). An energy-efficient and security aware route selection protocol for wireless sensor networks. Security and Communication Networks, 7(11), 2015–2038.CrossRefGoogle Scholar
  9. 9.
    Nakayama, H., Kurosawa, S., Jamalipour, A., Nemoto, Y., & Kato, N. (2009). A dynamic anomaly detection scheme for aodv-based mobile ad hoc networks. IEEE Transactions on Vehicular Technology, 58(5), 2471–2481.CrossRefGoogle Scholar
  10. 10.
    Buneman, P., Khanna, S., & Wang-Chiew, T. (2001). Why and where: A characterization of data provenance. In Database theory ICDT 2001 (pp. 316–330). Springer.Google Scholar
  11. 11.
    Zhou, W., Sherr, M., Tao, T., Li, X., Loo, B .T., & Mao, Y. (2010). Efficient querying and maintenance of network provenance at internet-scale. In Proceedings of the 2010 ACM SIGMOD international conference on management of data, ACM (pp. 615–626).Google Scholar
  12. 12.
    Chen, A., Wu, Y., Haeberlen, A., Zhou, W. & Loo, B. T. (2016). The good, the bad, and the differences: Better network diagnostics with differential provenance. In Proceedings of the 2016 conference on ACM SIGCOMM 2016 conference (pp. 115–128). ACM.Google Scholar
  13. 13.
    Zhou, W., Fei, Q., Narayan, A., Haeberlen, A., Loo, B. T., & Sherr, M. (2011). Secure network provenance. In Proceedings of the twenty-third ACM symposium on operating systems principles (pp. 295–310). ACM.Google Scholar
  14. 14.
    Zhou, W., Fei, Q., Sun, S., Tao, T., Haeberlen, A., Ives, Z., et al. (2011). Nettrails: A declarative platform for maintaining and querying provenance in distributed systems. In Proceedings of the 2011 ACM SIGMOD international conference on management of data ACM (pp. 1323–1326).Google Scholar
  15. 15.
    Wu, Y., Haeberlen, A., Zhou, W., & Loo, B. T. (2013). Answering why-not queries in software-defined networks with negative provenance. In Proceedings of the twelfth ACM workshop on hot topics in networks (p. 3). ACM.Google Scholar
  16. 16.
    Wu, Y., Zhao, M., Haeberlen, A., Zhou, W., & Loo, B. T. (2015). Diagnosing missing events in distributed systems with negative provenance. ACM SIGCOMM Computer Communication Review, 44(4), 383–394.CrossRefGoogle Scholar
  17. 17.
    Li, T., Ma, J., & Sun, C. (2015). Confidential reasoning and verification towards secure routing in ad hoc networks. In International conference on algorithms and architectures for parallel processing (pp. 449–462). Springer.Google Scholar
  18. 18.
    Haeberlen, A., Kouznetsov, P., & Druschel, P. (2007). Practical accountability for distributed systems. In ACM SIGOPS operating systems review (Vol. 41, pp. 175–188). ACM.Google Scholar
  19. 19.
    Gurney, A. J., Haeberlen, A., Zhou, W., Sherr, M., & Loo, B. T. (2011). Having your cake and eating it too: Routing security with privacy protections. In Proceedings of the 10th ACM workshop on hot topics in networks (p. 15).Google Scholar
  20. 20.
    Haeberlen, A., Avramopoulos, I. C., Rexford, J., & Druschel, P. (2009). Netreview: Detecting when interdomain routing goes wrong. NSDI, 2009, 437–452.Google Scholar
  21. 21.
    Hayajneh, T., Mohd, B. J., Imran, M., Almashaqbeh, G., & Vasilakos, A. V. (2016). Secure authentication for remote patient monitoring with wireless medical sensor networks. Sensors, 16(4), 424.CrossRefGoogle Scholar
  22. 22.
    Papadimitriou, A., Zhao, M., & Haeberlen, A. (2013). Towards privacy-preserving fault detection. In Proceedings of the 9th workshop on hot topics in dependable systems (p. 6). ACM.Google Scholar
  23. 23.
    Mohanapriya, M., & Krishnamurthi, I. (2014). Modified dsr protocol for detection and removal of selective black hole attack in manet. Computers & Electrical Engineering, 40(2), 530–538.CrossRefGoogle Scholar
  24. 24.
    Wang, W., Zeng, G., Yao, J., Wang, H., & Tang, D. (2012). Towards reliable self-clustering mobile ad hoc networks. Computers & Electrical Engineering, 38(3), 551–562.CrossRefGoogle Scholar
  25. 25.
    Liu, W., & Yu, M. (2014). Aasr: authenticated anonymous secure routing for manets in adversarial environments. IEEE Transactions on Vehicular Technology, 63(9), 4585–4593.CrossRefGoogle Scholar
  26. 26.
    Papadimitratos, P., & Haas, Z. J. (2002). Secure routing for mobile ad hoc networks. In The SCS commnication networks and distributed systems modeling and simulation conference (CNDS) (pp. 193–204), San Antonio, TX, 27–31 Jan 2002.Google Scholar
  27. 27.
    Sanzgiri, K., Dahill, B., Levine, B. N., Shields, C., & Royer, E. M. B. (2002). A secure routing protocol for ad hoc networks. In Proceedings of 10th IEEE international conference on network protocols (pp. 78–87). IEEE.Google Scholar
  28. 28.
    Balfanz, D., Smetters, D. K., Stewart, P., & Wong, H. C. (2002). Talking to strangers: Authentication in ad-hoc wireless networks. In NDSS, Citeseer.Google Scholar
  29. 29.
    Hayajneh, T., Almashaqbeh, G., & Ullah, S. (2015). A green approach for selfish misbehavior detection in 802.11-based wireless networks. Mobile Networks and Applications, 20(5), 623–635.CrossRefGoogle Scholar
  30. 30.
    Williams, D., & Sirer, E. G. (2004). Optimal parameter selection for efficient memory integrity verification using merkle hash trees. In Proceedings of third IEEE international symposium on network computing and applications, 2004 (NCA 2004) (pp. 383–388). IEEE.Google Scholar
  31. 31.
    Duan, J., Yang, D., Zhu, H., Zhang, S., & Zhao, J. (2014). TSRF: A trust-aware secure routing framework in wireless sensor networks. International Journal of Distributed Sensor Networks, 2014(3), 1–14.Google Scholar
  32. 32.
    Wang, B., Chen, X., & Chang, W. (2014). A light-weight trust-based qos routing algorithm for ad hoc networks. Pervasive and Mobile Computing, 13, 164–180.CrossRefGoogle Scholar
  33. 33.
    Li, T., Ma, J., & Sun, C. (2017). Netpro: detecting attacks in manet routing with provenance and verification. Science China Information Sciences, 60(11), 118101.CrossRefGoogle Scholar
  34. 34.
    Karp, B., & Kung, H.-T. (2000). GPSR: Greedy perimeter stateless routing for wireless networks. In Proceedings of the 6th annual international conference on Mobile computing and networking (pp. 243–254). ACM.Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2017

Authors and Affiliations

  1. 1.School of Cyber EngineeringXidian UniversityXi’anChina

Personalised recommendations