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Blockchain and federated Q-learning-based secure, fault tolerant, and energy efficient framework for ad hoc networks
PLOS One, Volume: 21, Issue: 3, Start page: e0342008
Swansea University Author:
Cheng Cheng
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© 2026 Tandon et al. This is an open access article distributed under the terms of the Creative Commons Attribution License.
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DOI (Published version): 10.1371/journal.pone.0342008
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 an...
| Published in: | PLOS One |
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| ISSN: | 1932-6203 |
| Published: |
Public Library of Science (PLoS)
2026
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| Online Access: |
Check full text
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| URI: | https://cronfa.swan.ac.uk/Record/cronfa71291 |
| 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 dynamic network show that the proposed model provides better performance in packet delivery, fewer false detections, and shorter recovery time in comparison to other systems. Furthermore, the proposed system holds significant promise for critical applications such as battlefield communication, disaster recovery, and remote monitoring, where reliable and secure networking is essential. The novelty of the work is the combination of a lightweight blockchain (MicroChain), Adaptive Cryptographic Engine (ACE), and federated Q-learning into one framework of ad hoc networks. The proposed framework provides high-security, effective resource usage, and responsiveness to the current network environment unlike earlier solutions, which focus on security, power usage, or fault tolerance separately. |
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| College: |
Faculty of Science and Engineering |
| Funders: |
The authors are funded by UKRI Grant EP/W020408/1 and Grant RS718 through the Doctoral Training Center at Swansea University. |
| Issue: |
3 |
| Start Page: |
e0342008 |

