Wireless Communications and Mobile Computing · 2021 · 58 citations · 42 references
ComputingComputer EngineeringComputer ScienceComputer SecurityMobile SecurityNetwork SecurityIntrusion DetectionIntrusion PreventionMobile Network SecurityWireless Network SecurityAd Hoc NetworkingAd Hoc NetworksBlackhole Attack DetectionDigital Signature ImplementationDigital Signature SchemesDistance-vector RoutingMobile Ad Hoc Network SecuritySecurity Protocols For Wireless Networks
In mobile ad hoc networks (MANETs), mobile devices connect with other devices wirelessly, where there is no central administration. They are prone to different types of attacks such as the black hole, insider, gray hole, wormhole, faulty node, and packet drop, which considerably interrupt to perform secure communication. This paper has implemented the denial‐of‐service attacks like black hole attacks on general‐purpose ad hoc on‐demand distance vector (AODV) protocol. It uses three approaches: normal AODV, black hole AODV (BH_AODV), and detected black hole AODV (D_BH_AODV), wherein we observe that black holes acutely degrade the performance of networks. We have detected the black hole attacks within the networks using two techniques: (1) intrusion detection system (IDS) and (2) encryption technique (digital signature) with the concept of prevention. Moreover, normal AODV, BH_AODV, and D_BH_AODV protocols are investigated for various quality of service (QoS) parameters, i.e., packet delivery ratio (PDR), delay, and overhead with varying the number of nodes, packet sizes, and simulation times. The NS2 software has been used as a simulation tool to simulate existing network topologies, but it does not contain any mechanism to simulate malicious protocols by itself; therefore, we have developed and implemented a D_BH_AODV routing protocol. The outcomes show that the proposed D_BH_AODV approach for the PDR value delivers around 40 to 50% for varying nodes and packets. In contrast, the delay decreases from 300 to 100 ms and 150 to 50 ms with an increase in the number of nodes and packets, respectively. Furthermore, the overhead changes from 1 to 3 for various nodes and packet values. The outcome of this research proves that the black hole attack degrades the overall performance of the network, while the D_BH_AODV enhances the QoS performance since it detects the black hole nodes and avoids them to establish the communication between nodes.
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