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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM64513
Volume:
10 |
6 |
Jun 2026
Pages:
1-6
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Commerce Computer Application
Sri Krishna Arts and Science College
The proliferation of Internet of Things (IoT) devices necessitates a shift from traditional centralized cloud processing to distributed network architectures, leading to the creation of Edge of Things (EoT) networks. While Edge Computing effectively reduces latency and computational burdens for time-sensitive applications like smart healthcare and smart transportation, its distributed nature introduces significant challenges regarding security, privacy, and identity management. This paper explores the critical convergence of Blockchain, Artificial Intelligence (AI), and Decentralized Identity (DI) to establish secure, scalable, and trustworthy systems for edge computing environments. Blockchain provides decentralization, immutability, and traceability, addressing vulnerabilities inherent in EoT systems. Decentralized Identity (DI), specifically Self-Sovereign Identity (SSI), restores user control over verifiable credentials (VCs) and Decentralized Identifiers (DIDs), creating a foundation of verifiable trust. Furthermore, AI offers the necessary intelligence for advanced fraud detection, autonomous decision-making, and process optimization within these complex, latency-sensitive infrastructures. This integrated approach not only enhances performance but also prepares the ecosystem for future threats, such as those posed by quantum computing, through solutions like Quantum Key Distribution (QKD).
KEYWORDS
The integration of Blockchain, AI, and Decentralized Identity marks a foundational shift in addressing the security and privacy challenges inherent in distributed Edge Computing environments. Blockchain provides the core trust layer via immutability and decentralization, mitigating threats like single points of failure and malicious data injection. SSI leverages this foundation to empower users and autonomous AI agents with verifiable, user-controlled identities (DIDs and VCs). AI enhances this framework by providing the analytical capabilities for real-time fraud detection (ML), transparency (XAI), and optimized privacy-preserving processing (federated learning). While challenges related to latency, storage, and energy efficiency persist, targeted architectural solutions, including consortium blockchains and optimized cryptography, demonstrate pathways toward scalable and high-performing BEoT environments. Crucially, anticipating quantum threats with solutions like QKD and post-quantum standards ensures the longevity and cryptographic resilience of this emerging Global Trust Infrastructure. The future of edge computing is defined by this convergence, moving beyond mere connectivity to establishing a reliable, auditable, and human-centric digital society where trust is a computable property. This holistic architecture ensures that technology acts as a tool of liberation, safeguarding individual autonomy and accountability in an increasingly automated and interconnected world.
1. https://www.sciencedirect.com/science/article/abs/pii/S1574013724000510 2. https://www.mdpi.com/1999-5903/17/1/45 3. https://www.embedded.com/embedding-blockchain-for-enhanced-security-in-iot-networks/ 4. https://www.researchgate.net/publication/349469626_Embedding_Blockchain_Technology_Into_IoT_for_Security_A_Survey 5. Exploring the integration of edge computing and blockchain IoT: Principles, architectures, security, and applications by tri ngugen, journal of network and computer applications, volume 226, June 2024 6. Blockchain and edge computing technology enabling organic agricultural supply chain: A framework solution to trust crisis by sensen hu, computers and industrial engeering , volume 153, march 2021
Publication Date
6/4/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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