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Detecting and Predicting Malicious Nodes in Mobile Ad-hoc Networks using a Secure Technique
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 184 - Number 3 |
| Year of Publication: 2022 |
| Authors: Imran Khan, Pratik Gite |
10.5120/ijca2022921988
|
Imran Khan, Pratik Gite . Detecting and Predicting Malicious Nodes in Mobile Ad-hoc Networks using a Secure Technique. International Journal of Computer Applications. 184, 3 ( Mar 2022), 15-19. DOI=10.5120/ijca2022921988
Abstract
Mobile Ad Hoc Networking (MANET) is a rapidly growing area of interest in the realm of communication frameworks. Due to the fact that the MANET lacks a basis, it exhibits the dynamic character of a self-assertive network architecture. Security concerns are critical in these networks. Nodes in MANETs may launch a variety of assaults or become conspicuously self-centered in order to preserve their advantage. These nodes may be considered malicious. Identification of such malicious nodes is critical for the successful operation of MANETs. A collection of networks has been presented, but each one has its own set of constraints. The scope of this proposal is to do research on black hole, worm hole collaborative malevolent, and flooding attacks, and to establish a network of counteractive action by using responsive directing conventions. For execution analysis and replication, an AODV, NS-2 organized test network is used. To prevent black hole, worm hole collaboration malevolent, and flooding attacks, a countermeasure is used in which the Trust value is calculated based on the route request, route response, and information packet. Following the count, place stock in values ranging from 0 to 1. If the trust esteem is more than 0.5, the node is solid and permits access to the network as a whole. The suggested convention secure Ad hoc On-demand distance vector (SAODV) is evaluated in terms of network execution. When compared to the usual AODV convention, the result reveals execution change. By increasing the duration a dip in throughput, SAODV's throughput is superior to that of joint malicious assault AODV and current protocol. SAODV's packet delivery ratio is superior to that of joint malicious attack AODV and the established AODV protocol. SAODV's End to End Delay is superior than joint malicious attack AODV and the current AODV protocol.
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