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Research Paper | Computer Science and Engineering | Volume 15 Issue 3, March 2026 | Pages: 270 - 276 | India
A Hybrid Blockchain - AI Model for Secure Identity Management and Cryptographic Key Distribution in Large-Scale IoD Networks
Abstract: Large and distributed Internet-of-Drones (IoD) ecosystems are increasingly deployed for surveillance, logistics, agricultural monitoring, disaster response, and defense. As deployments grow to thousands of drones across heterogeneous trust domains, traditional Public Key Infrastructure (PKI) architectures struggle to deliver decentralization, mobility-aware trust, and quantum-resilient keying (Awasthi et al., 2023; Alshahrani & Alghamdi, 2024). This paper presents H-BAIKD, a Hybrid Blockchain?AI Keying and Identity Distribution framework that integrates decentralized identity, hybrid post-quantum cryptography, federated anomaly detection, and reinforcement-learning-based adaptive key lifecycle management. The architecture mitigates impersonation, Sybil, replay, GPS spoofing, data-poisoning, and quantum-era cryptanalytic threats (Jiang et al., 2025; McKeen et al., 2024). Comprehensive evaluations using ns-3, Hyperledger Fabric, and the OpenQuantumSafe suite demonstrate significant improvements in authentication latency, post-quantum performance, trust propagation, and resilience under adversarial conditions. The results indicate that integrating blockchain, PQC, and AI offers a critical security foundation for next-generation IoD swarms operating in dynamic, resource-constrained, and hostile environments.
Keywords: Internet of Drones, blockchain identity management, post quantum cryptography, AI based key management, secure drone communication
How to Cite?: Anamika Dixit, Seema Premnath Dhande, "A Hybrid Blockchain - AI Model for Secure Identity Management and Cryptographic Key Distribution in Large-Scale IoD Networks", Volume 15 Issue 3, March 2026, International Journal of Science and Research (IJSR), Pages: 270-276, https://www.ijsr.net/getabstract.php?paperid=SC26211090633, DOI: https://dx.doi.org/10.21275/SC26211090633