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An Effective Scheme to Mitigate Blackhole Attack in Mobile Ad Hoc Networks

Part of the Lecture Notes in Electrical Engineering book series (LNEE,volume 869)


MANET refers to a mobile ad hoc network, which is self-configured without having a fixed base. It has been used in various fields for various purposes like military, local conferences, and the movable of information. However, due to the lack of built-in security, safety is a significant concern in the MANET. There are various types of attacks which are possible on MANETs. One of the attack is a Blackhole attack. It is an active attack in which a malicious node shows itself as the shortest route and absorbs the packet just like a blackhole does in-universe. In this paper, a proposed technique has used a trust-based fuzzy method based on auditing of energy, the Trust of a neighbouring node, check for the integrity of packets, and authentication of the Node Member. Trust values in the fuzzy logic range from 0 to 1. If node trust value is higher than or equal to 0.6, then the node is trusted, and its type of node taken in our scenario for communication between source to destination. If the node trust rate on the routing table is less than 0.6, that means the node is a blackhole node, and its type node does not consider a safe route, in this paper proposed a method, i.e., Trust-based Fuzzy Ad hoc On-Demand Distance Vector (TFAODV), to an attack scenario. This paper is improved results in terms of throughput, packet delivery ratio, end-to-end delay, shows the throughput improvement, and found to be 1441 kbps, packet delivery ratio enhancement of 57.10%, and delay decrease of 52% from Blackhole Ad hoc On-Demand Distance Vector (BAODV). Therefore, the proposed protocol covers the way and possesses the potential to secure the MANET.


  • Blackhole attack
  • AODV
  • Trust authentication
  • Trust of a neighbouring node

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Correspondence to Mukul Shukla .

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Shukla, M., Joshi, B.K. (2022). An Effective Scheme to Mitigate Blackhole Attack in Mobile Ad Hoc Networks. In: Patgiri, R., Bandyopadhyay, S., Borah, M.D., Emilia Balas, V. (eds) Edge Analytics. Lecture Notes in Electrical Engineering, vol 869. Springer, Singapore.

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  • Print ISBN: 978-981-19-0018-1

  • Online ISBN: 978-981-19-0019-8

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