Citation: Proceedings of the 2017 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 11, pages 797–802 (2017)
Abstract. A mobile ad hoc network (MANET) is a collection of mobile nodes that do not need to rely on a pre-existing network infrastructure or centralized administration. Securing MANETs is a serious concern as current research on MANETs continues to progress. Each node in a MANET acts as a router, forwarding data packets for other nodes and exchanging routing information between nodes. It is this intrinsic nature that introduces the serious security issues to routing protocols. A black hole attack is one of the well-known security threats for MANETs. A black hole is a security attack in which a malicious node absorbs all data packets by sending fake routing information and drops them without forwarding them. In order to defend against a black hole attack, in this paper we propose a new threshold-based black hole attack prevention method. To investigate the performance of the proposed method, we compared it with existing methods. Our simulation results show that the proposed method outperforms existing methods from the standpoints of black hole node detection rate, throughput, and packet delivery rate.
- F.-H. Tseng, L.-D. Chou, and H.-C. Chao, “A Survey of Black Hole At- tacks in Wireless Mobile Adhoc Networks,” Human-centric Computing and Information Science, vol.1, no.1, pp.1-16, Dec. 2011.
- A. Sherif, M. Elsabrouty, and A. Shoukry, “A Novel Taxon- omy of Black-Hole Attack Detection Techniques in Mobile Ad- hoc Network (MANET),” in Proc. IEEE International Confer- ence on Computational Science and Engineering, pp.346-352, http://dx.doi.org/10.1109/CSE.2013.60, Dec. 2013.
- C. Perkins, E. Belding-Royer, and S. Das, “Ad-hoc On-Demand Distance Vector (AODV) Routing,” RFC3561, http://dx.doi.org/10.17487/RFC3561, https://www.ietf.org/rfc/rfc3561.txt.
- L. Tamilselvan and V. Sankaranarayanan, “Prevention of Black-hole Attack in MANET,” in Proc. IEEE International Conference on Wireless Broadband and Ultra Wideband Communications, p. 21, http://dx.doi.org/10.1109/AUSWIRELESS.2007.61, Aug. 2007.
- D. Kshirsagar and A. Patil, “Blackhole Attack Detection and Prevention by Real Time Monitoring,” in Proc. IEEE International Conference on Computing, Communications and Networking Technologies, pp.1-5, http://dx.doi.org/10.1109/ICCCNT.2013.6726597, July 2013.
- S. Jain and A. Khunteta, “Detecting and Overcoming Blackhole Attack in Mobile Adhoc Network,” in Proc. IEEE International Conference on Green Computing and Internet of Things, pp. 225-229, http://dx.doi.org/10.1109/ICGCIoT.2015.7380462, Oct. 2015.
- S. Kurosawa, H. Nakayama, N. Kato, and A. Jamalipour, “Detecting Blackhole Attack on AODV-Based Mobile Adhoc Networks by Dynamic Learning Method,” International Journal of Network Security, vol. 5, no. 3, pp. 338-346, Nov. 2007.
- P. N. Raj and P. B. Swadas, “DPRAODV: A Dynamic Learning System against Blackhole Attack in AODV Based MANET,” International Journal of Computer Science Issues, vol.2, pp.54-59, Aug. 2009.
- S. Tan and K. Kim,“Secure Route Discovery for Preventing Black Hole Attacks on AODV-Based MANETs,” in Proc. IEEE International Conference on High Performance Computing and Communications and IEEE International Conference on Embedded and Ubiquitous Computing, pp.1159-1164, http://dx.doi.org/10.1109/HPCC.and.EUC.2013.164, Nov. 2013.
- DARPA, “The Network Simulator - ns-2” (online), available from (http://www.isi.edu/nsnam/ns/) (accessed 2017-04-20).