Detecting and Predicting Malicious Nodes in Mobile Ad-Hoc Networks using a Secure Technique

Mobile Ad Hoc Networking (MANET) is a rapidly growing area of interest in the realm of communication frameworks. Because 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 attacks or become conspicuously self-centred to maintain 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 conduct research on black hole, wormhole, collaborative malevolent, and flooding attacks, and to establish a network of counteractive measures using responsive directing conventions. For execution analysis and replication, an AODV, NS-2 organised test network is used. To prevent black hole, wormhole, malevolent, and flooding attacks, a countermeasure is employed that calculates the Trust value 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 performance. When compared to the standard AODV convention, the results reveal a notable difference in execution. By increasing the duration of a dip in throughput, SAODV achieves a throughput superior to that of the joint malicious assault AODV and the current protocol. SAODV’s packet delivery ratio is superior to that of the joint malicious attack AODV and the established AODV protocol. SAODV’s end-to-end delay is superior to the joint malicious attack AODV and the current AODV protocol.

Authors

Publication Details

Journal
International Journal of Emerging Science and Engineering
Published
2025-08-25
DOI
https://doi.org/10.35940/ijese.d2526.13090825
Primary Topic
Opportunistic and Delay-Tolerant Networks
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Detecting and Predicting Malicious Nodes in Mobile Ad-Hoc Networks using a Secure Technique

Imran Khan, Pratik Gite
International Journal of Emerging Science and Engineering
Opportunistic and Delay-Tolerant Networks
article

Detecting and Predicting Malicious Nodes in Mobile Ad-Hoc Networks using a Secure Technique

Imran Khan, Pratik Gite
article en

Abstract

Mobile Ad Hoc Networking (MANET) is a rapidly growing area of interest in the realm of communication frameworks. Because 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 attacks or become conspicuously self-centred to maintain 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 conduct research on black hole, wormhole, collaborative malevolent, and flooding attacks, and to establish a network of counteractive measures using responsive directing conventions. For execution analysis and replication, an AODV, NS-2 organised test network is used. To prevent black hole, wormhole, malevolent, and flooding attacks, a countermeasure is employed that calculates the Trust value 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 performance. When compared to the standard AODV convention, the results reveal a notable difference in execution. By increasing the duration of a dip in throughput, SAODV achieves a throughput superior to that of the joint malicious assault AODV and the current protocol. SAODV’s packet delivery ratio is superior to that of the joint malicious attack AODV and the established AODV protocol. SAODV’s end-to-end delay is superior to the joint malicious attack AODV and the current AODV protocol.

International Journal of Emerging Science and EngineeringVol. 13(9)
Openalex Percentile: Top 75%
Opportunistic and Delay-Tolerant Networks
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.