Blockchain and federated Q-learning-based secure, fault tolerant, and energy efficient framework for ad hoc networks
Righa Tandon, P. K. Gupta, Xiaochun Cheng
TL;DR
This paper introduces a secure and energy-efficient framework for ad hoc networks using blockchain and federated Q-learning to improve communication reliability and fault tolerance.
Contribution
The novelty is combining lightweight blockchain, adaptive cryptography, and federated Q-learning in a single framework for ad hoc networks.
Findings
The framework improves packet delivery and reduces false detections in dynamic networks.
It achieves shorter recovery times compared to existing systems.
The model is suitable for critical applications like disaster recovery and battlefield communication.
Abstract
An ad hoc network plays a critical role in enabling communication in environments where deploying fixed infrastructure is impractical or infeasible. However, their dynamic topology and decentralized nature make them highly susceptible to failures and security threats. This paper proposes a robust and intelligent framework that addresses these challenges by integrating secure communication, fault tolerance, and energy efficiency. The proposed model makes use of blockchain technology to encourage trust between nodes, works with several nodes in the network to spot their unusual behavior, and uses federated Q-learning for adaptive threat response. The key components of the proposed framework, i.e., identity validation, trust scoring, distributed anomaly detection, and autonomous role management, make the system stable, robust, and energy-efficient. Simulation results of 500 nodes in a…
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Taxonomy
TopicsMobile Ad Hoc Networks · Vehicular Ad Hoc Networks (VANETs) · Blockchain Technology Applications and Security