EDGChain-E: A Decentralized Git-Based Framework for Versioning Encrypted Energy Data

2025-07-02

AI Summary

To address challenges in secure management, version control, and multi-stakeholder collaboration for encrypted energy data in decentralized environments, this paper proposes a lightweight framework integrating blockchain, IPFS, and DAO-based governance. Methodologically, it introduces a Git-inspired encrypted data versioning mechanism, employs Merkle tree–embedded hashes for tamper-proof change auditing, and incorporates fine-grained encrypted patching to preserve data privacy. At the governance level, a DAO enables collaborative decision-making among utilities, researchers, and regulators without exposing sensitive information. The key contributions are: (i) the first practical implementation of the FAIR principles—Findability, Accessibility, Interoperability, and Reusability—in encrypted energy data governance, ensuring provenance, traceability, and integrity; and (ii) empirical validation demonstrating effective support for data sharing and research reproducibility in smart grid monitoring, demand forecasting, and peer-to-peer energy trading scenarios.

Technology Category

• Data Mining & Knowledge Management: Representing, Reasoning, and Using Provenance, Trust
• Search and Optimization: Distributed Search
• Application Domains: Internet of Things, Sensor Networks & Smart Cities

Application Category

• Security and Privacy: Data transparency and provenance
• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• Semantics and Knowledge: Provenance, trust, security and privacy, and ethical issues in managing semantic data

Abstract

This paper proposes a new decentralized framework, named EDGChain-E (Encrypted-Data-Git Chain for Energy), designed to manage version-controlled, encrypted energy data using blockchain and the InterPlanetary File System. The framework incorporates a Decentralized Autonomous Organization (DAO) to orchestrate collaborative data governance across the lifecycle of energy research and operations, such as smart grid monitoring, demand forecasting, and peer-to-peer energy trading. In EDGChain-E, initial commits capture the full encrypted datasets-such as smart meter readings or grid telemetry-while subsequent updates are tracked as encrypted Git patches, ensuring integrity, traceability, and privacy. This versioning mechanism supports secure collaboration across multiple stakeholders (e.g., utilities, researchers, regulators) without compromising sensitive or regulated information. We highlight the framework's capability to maintain FAIR-compliant (Findable, Accessible, Interoperable, Reusable) provenance of encrypted data. By embedding hash-based content identifiers in Merkle trees, the system enables transparent, auditable, and immutable tracking of data changes, thereby supporting reproducibility and trust in decentralized energy applications.

Problem

• Manages version-controlled encrypted energy data securely
• Ensures data integrity and privacy in energy operations
• Supports FAIR-compliant provenance for decentralized energy applications

Innovation

• Decentralized Git-based versioning for encrypted data
• DAO-managed collaborative data governance
• Merkle trees for transparent data change tracking