Malicious Node Detection in MANETs using Trust Based Approach

Abstract

Mobile Ad-hoc Networks (MANETs) are decentralized wireless networks. The characteristics of MANETs are dynamic topology and a lack of fixed infrastructure. These features make them highly flexible and expose them to significant security vulnerabilities. To overcome these vulnerabilities,our energy composite trust model calculates a trust score for each node based on its packet forwarding behaviour and energy consumption. It also incorporates a direct mechanism for identifying flooding attacks by monitoring packet traffic rates. The proposed system was implemented and evaluated using the NS-3 simulator. Simulation results in NS-3 demonstrate that the proposed method effectively isolates malicious nodes.

Introduction

Mobile Ad-Hoc Networks (MANETs) are decentralized wireless networks with dynamic topology and no centralized control, making them vulnerable to attacks like packet dropping, resource depletion, and flooding-based Denial-of-Service (DoS). This paper proposes a trust-based intrusion detection system that enhances MANET security by monitoring three key trust metrics: forwarding behavior, energy consumption, and flooding attack detection.

• Forwarding Trust measures the ratio of packets successfully forwarded versus dropped by a node.

• Energy Trust monitors abnormal energy consumption, penalizing nodes that consume energy excessively, which may indicate malicious or selfish behavior.

• Flooding Detection uses a threshold-based mechanism to identify nodes sending unusually high packet rates, signaling a flooding attack.

The system calculates a combined trust score (weighted 70% energy trust and 30% forwarding trust). Nodes falling below a trust threshold (0.7) are classified as malicious and isolated by disabling their network participation.

A simulation using 20 mobile nodes (with one malicious node exhibiting 70% packet dropping and flooding behavior) demonstrated that the trust model effectively identified and isolated the malicious node. The malicious node’s trust score declined steadily due to packet dropping, high energy consumption, and flooding, resulting in successful removal from the network. Normal nodes maintained consistently high trust scores.

Conclusion

This paper presented a trust model that uses forwarding behaviour and energy consumption for trust metrics and integrates a specific flood detection mechanism that decreases the malicious node\'s trust. The NS-3 simulation results confirmed that the system can successfully identify a node performing simultaneous packet dropping, energy drain, and flooding attacks, and isolate it from the network to protect other nodes.

References

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Copyright

Copyright © 2025 Dr. K. Suresh Babu, K. Sai Charan. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.