A Novel Node Collusion Method for Isolating Sinkhole Nodes in Mobile Ad Hoc Cloud

  • Immanuel Johnraja Jebadurai
  • Elijah Blessing Rajsingh
  • Getzi Jeba Leelipushpam Paulraj
Conference paper
First Online:
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 645)

Abstract

Cloud computing combined with mobile technology provides immense computing capabilities. The services and applications can be accessed anywhere and anytime. The required services for mobile users are offered on runtime with high reliability and availability by the mobile ad hoc cloud. Mobile devices communicate with each other through multi-hop communication using routing protocols. Heterogeneity of the devices, limited battery life, and mobility of the nodes are the salient features of the mobile devices. These characteristics impose greater challenges in terms of routing, security, and privacy. Any attacker node can advertise false routing information to lure other nodes to use its service. Such nodes are called sinkhole nodes. Sinkhole nodes need to be isolated from the mobile cloud as early as possible with high precision to provide uninterrupted service to other mobile users. This paper proposes a node collusion method for the detection and isolation of sinkhole nodes. The proposed method has been implemented using NS-2 simulator. The results were obtained. The results were compared with the existing state-of-the-art algorithms for sinkhole detection. It is found that the proposed method outperforms other methods in terms of detection time, false-positive ratio, routing overhead, and packet delivery ratio.

Keywords

Mobile cloud Cloud computing Sinkhole attack Collusion RREQ RREP DSR Security 
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Reference

  1. 1.
    Fernando, N., Loke, S.W., Rahayu, W.: Mobile cloud computing: a survey. Future Gener Comput Syst 29(1), 84–106 (2013)CrossRefGoogle Scholar
  2. 2.
    Huerta-Canepa, G., Lee, D.: A virtual cloud computing provider for mobile devices. In: Proceedings of the 1st ACM Workshop on Mobile Cloud Computing and Services: Social Networks and Beyond. ACM (2010)Google Scholar
  3. 3.
    Rahimi, M.Reza, et al.: Mobile cloud computing: a survey, state of art and future directions. Mobile Netw. Appl. 19(2), 133–143 (2014)MathSciNetCrossRefGoogle Scholar
  4. 4.
    Dinh, H.T., et al.: A survey of mobile cloud computing: architecture, applications, and approaches. Wirel. Commun. Mobile Comput. 13(18), 1587–1611 (2013)Google Scholar
  5. 5.
    Othman, M., Xia, F., Abdul Nasir Khan: Context-aware mobile cloud computing and its challenges. IEEE Cloud Comput. 2(3), 42–49 (2015)Google Scholar
  6. 6.
    Yaqoob, I., et al.: Mobile ad hoc cloud: a survey. Wirel. Commun. Mobile Comput. 16(16), 2572–2589 (2016)Google Scholar
  7. 7.
    Bansal, S., Baker, M.: Observation-based cooperation enforcement in ad hoc networks. Research Report cs. NI/ 0307012, Stanford UniversityGoogle Scholar
  8. 8.
    Gandhewar, N., Patel, R.: Detection and prevention of sinkhole attack on AODV protocol in mobile adhoc network. In: 2012 Fourth International Conference on Computational Intelligence and Communication Networks (CICN), pp. 714–718. IEEE (2012)Google Scholar
  9. 9.
    Gagandeep, A., Kumar, P.: Analysis of different security attacks in MANETs on protocol stack A-review. Int. J. Eng. Adv. Technol. (IJEAT) 1(5), 269–275 (2012)Google Scholar
  10. 10.
    Kim, G., Han, Y., Kim, S.: A cooperative-sinkhole detection method for mobile ad hoc networks. Int. J. Electron. Commun. 64, 390–397 (2010)Google Scholar
  11. 11.
    Girish Kumar, V., Rachit Jain: A table driven search approach for revelation and anticipation of sinkhole attack in MANET. Int. J. Res. Eng. Technol. 05(08), 20–25 (2016)Google Scholar
  12. 12.
    Li, X., Jia, Z., Zhang, P., Zhang, R., Wang, H.: Trust-based on-demand multipath routing in mobile ad hoc networks. IET Inf. Secur. 4(4), 212–232 (2010)Google Scholar
  13. 13.
    Mitchell, R., Chen, R.: A survey of intrusion detection in wireless network applications. Comput. Commun. 42, 1–23 (2014)CrossRefGoogle Scholar
  14. 14.
    Sen, S., Clark, J.A., Tapiador, J.E.: Power-aware intrusion detection in mobile ad hoc networks. In: Proceedings of the Ad Hoc Networks. Lecture Notes of the Institute of Computer Sciences, Social Informatics and Telecommunications Engineering, vol. 28, pp. 224–239. Springer (2010)Google Scholar
  15. 15.
    Vishnu, K., Paul, A.J.: Detection and removal of cooperative black/gray hole attack in mobile ad hoc networks. Int. J. Comput. Appl. 1(22), 38–42 (2010)Google Scholar
  16. 16.
    Stafrace, S.K., Antonopoulos, N.: Military tactics in agent-based sinkhole attack detection for wireless ad hoc networks. Comput. Commun. 33, 619–638 (2010)CrossRefGoogle Scholar
  17. 17.
    Shafiei, H., Khonsari, A., Derakhshi, H., Mousavi, P.: Detection and mitigation of sinkhole attacks in wireless sensor networks. J. Comput. Syst. Sci. 80(3), 644–653 (2014)CrossRefMATHGoogle Scholar
  18. 18.
    Sarika, S., Pravin, A., Vijayakumar, A., Selvamani, K.: Security issues in mobile ad hoc networks. Proc. Comput. Sci. 92, 329–335 (2016)CrossRefGoogle Scholar
  19. 19.
    Su, M.-Y.: Prevention of selective black hole attacks on mobile ad hoc networks through intrusion detection systems. Comput. Commun. 34, 107–117 (2011)CrossRefGoogle Scholar
  20. 20.
    Mitrokotsa, A., Dimitrakakis, C.: Intrusion detection in MANET using classification algorithms: the effects of cost and model selection. Ad Hoc Netw. 11(1), 226–237 (2013)CrossRefGoogle Scholar
  21. 21.
    Vennila, G., Arivazhagan, D., Manickasankari, N.: Prevention of co-operative black hole attack in manet on DSR protocol using cryptographic algorithm. Int. J. Eng. Technol. (IJET) 6(5), 2401 (2014)Google Scholar
  22. 22.
    Sanchez-Casado, L., Macia-Fernandez, G., Garcia-Teodoro, P., Aschenbruck, N.: Identification of contamination zones for sinkhole detection in MANETs. J. Netw. Comput. Appl. 54, 62–77 (2015)CrossRefGoogle Scholar
  23. 23.
    Thanachai, T., Tapanan, Y., Punthep, S.: Adaptive sinkhole detection on wireless ad hoc networks. In: Proceedings of IEEE aerospace conference, 4–11. IEEE, NJ, USA (2006)Google Scholar
  24. 24.
    Kim, G., Han, Y., Kim, S.: A cooperative-sinkhole detection method for mobile ad hoc networks. AEU-Int. J. Electron. Commun. 64(5), 390–397 (2010)CrossRefGoogle Scholar
  25. 25.
    Mohanapriya, M., Krishnamurthi, I.: Modified DSR protocol for detection and removal of selective black hole attack in MANET. Comput. Electr. Eng. 40(2), 530–538 (2014)CrossRefGoogle Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  • Immanuel Johnraja Jebadurai
    • 1
  • Elijah Blessing Rajsingh
    • 1
  • Getzi Jeba Leelipushpam Paulraj
    • 1
  1. 1.Karunya UniversityCoimbatoreIndia

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