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Sponsored Artificial Intelligence: A Modern Approach, Global Edition Artificial Intelligence: A Modern Approach, Global Edition

Author

Weiwei Jiang

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Open access 2026

ILAGKDF-IoD: An Intelligent Lightweight Authentication and Group Key Distribution Framework for Covert Communications in Next-Generation Internet of Drones Networks

The Internet of Drones (IoD) is an emerging technology for next-generation intelligent wireless networks, enabling applications such as smart-city surveillance, intelligent transportation, environmental monitoring, disaster management, and autonomous delivery. However, the highly dynamic and resource-constrained nature of IoD networks, together with the open broadcast characteristics of wireless communication, makes secure and privacy-preserving authentication challenging. In particular, identity disclosure, replay, impersonation, message modification, passive eavesdropping, and unauthorized access can compromise trusted communication among drones, Ground Station Servers (GSSs), Network Administrators (NAs), and Mobile Users (MUs). To address these challenges, this paper proposes an Intelligent Lightweight Authentication and Group Key Distribution Framework for Covert Communications in Next-Generation Internet of Drones Networks (ILAGKDF-IoD). The proposed scheme integrates lightweight hash/HMAC and bitwise XOR operations with dynamic group-key distribution to provide efficient authentication, anonymous identity management, and secure group communication while reducing the computational cost on resource-constrained drones. The security of ILAGKDF-IoD is evaluated through formal analysis under the Random Oracle Model (ROM) and comprehensive informal security analysis. The results demonstrate resistance to replay, impersonation, message modification, identity-disclosure, and passive-eavesdropping attacks, while providing conditional anonymity, traceability, unlinkability, forward secrecy, and backward secrecy. Performance evaluation shows that the proposed scheme significantly reduces computational cost by 28.57%-84.42% compared with the considered existing authentication schemes, demonstrating its computational efficiency and suitability for dynamic IoD environments. It provides a lightweight authentication and group-key management foundation for secure and privacy-preserving communications in intelligent covert-communication-enabled 5G/B5G/6G IoD networks.

P. Tiwari, Animesh Tripathi, Rajkumar Singh Rathore et al. · 0 citations
2026

Confidence-Aware Federated Learning for Smart Load Characterization in Cyber-Physical DER Systems

The integration of smart meters into residential environments has allowed smooth collection of electricity consumption data, which is critical for demand response and coordinated operation in cyber-physical distributed energy resource systems. However, existing centralized methods of consumer characteristic identification pose significant risks to data privacy and confidentiality. Furthermore, the inherent limitations imposed due to noisy data cause a steep degradation in the accuracy and system-level decision-making. Addressing the issues of accuracy and data confidentiality, this paper proposes a confidence-aware federated learning framework for privacy-preserving inference of electricity consumer characteristics from raw smart meter data. The proposed method employs decentralized retention of smart meter data, using federated learning to refine network performance while ensuring that raw data remain localized at the client level. By evaluating a combined distribution of noisy and clean labels, erroneous data points are identified and excluded, thereby enhancing the model's efficacy and robustness. The effectiveness of the approach is validated using the Irish Commission for Energy Regulation dataset. The proposed framework demonstrates notable improvements, achieving an average gain of 3.97% in accuracy and 3.68% in MCC score compared to state-of-the-art methods, while maintaining strong data privacy guarantees.

V. K. Singh, Vins Patel, Neeraj Jain et al. · 0 citations

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