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Decentralized Identity Management via Blockchain-Based Smart Contracts: A Cryptographic Self-Sovereign Framework

Authors
  • Harika Naidu Beesabathuni

    Author

Keywords:
Decentralized Identity, Blockchain, Smart Contracts, Ethereum, InterPlanetary File System (IPFS), Threshold Cryptography
Abstract

This research presents a novel decentralized identity management system leveraging Ethereum smart contracts and cryptographic protocols to enable self-sovereign digital identities. Traditional centralized identity solutions pose risks related to data privacy, security, and user autonomy. To address these limitations, we propose a blockchain-based architecture integrating smart contracts for identity governance, IPFS for decentralized attribute storage, and threshold cryptography for private data recovery. Our dual-contract model (Identity Contract and Recovery Contract) facilitates secure identity creation, verifiable attribute attestation, and robust key recovery through social consensus. We introduce a privacy-preserving mechanism using encryption-key splitting among trusted peers to enable recovery of encrypted off-chain data. Implementation uses Web3.js, Solidity, and QR-code-based communication, abstracting cryptographic complexities from end-users. Security analysis addresses replay, man-in-the-middle, Sybil, and multi-user compromise attacks with mitigations including challenge-response authentication and time-delayed contract execution. This work contributes a cryptographically secure, user-centric identity framework ensuring data sovereignty, recoverability, and interoperability within the Ethereum ecosystem.

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Published
2026-08-22
Section
Articles
License

Copyright (c) 2026 International Journal of Intelligent Systems and Data Science

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
H. N. Beesabathuni, “Decentralized Identity Management via Blockchain-Based Smart Contracts: A Cryptographic Self-Sovereign Framework”, Int. J. Intell. Syst. Data Sci., vol. 1, no. 4, Aug. 2026, doi: 10.67231/s2b5mw29.