A Blockchain-based Approach for Data Accountability and Provenance Tracking (1706.04507v1)

Abstract: The recent approval of the General Data Protection Regulation (GDPR) imposes new data protection requirements on data controllers and processors with respect to the processing of European Union (EU) residents' data. These requirements consist of a single set of rules that have binding legal status and should be enforced in all EU member states. In light of these requirements, we propose in this paper the use of a blockchain-based approach to support data accountability and provenance tracking. Our approach relies on the use of publicly auditable contracts deployed in a blockchain that increase the transparency with respect to the access and usage of data. We identify and discuss three different models for our approach with different granularity and scalability requirements where contracts can be used to encode data usage policies and provenance tracking information in a privacy-friendly way. From these three models we designed, implemented, and evaluated a model where contracts are deployed by data subjects for each data controller, and a model where subjects join contracts deployed by data controllers in case they accept the data handling conditions. Our implementations show in practice the feasibility and limitations of contracts for the purposes identified in this paper.

• The paper introduces blockchain-based smart contracts to enforce GDPR-compliant data accountability and provenance tracking.
• It compares three contract models, balancing detailed subject-specific controls with scalable aggregate approaches.
• The study benchmarks gas usage on Ethereum, highlighting trade-offs between precision in policy enforcement and operational costs.

An Analysis of a Blockchain-based Approach for Data Accountability and Provenance Tracking

The paper, "A Blockchain-based Approach for Data Accountability and Provenance Tracking," authored by Ricardo Neisse, Gary Steri, and Igor Nai-Fovino, addresses the challenge of ensuring compliance with the GDPR's data protection requirements through a novel application of blockchain technology. The paper investigates the potential integration of blockchain to facilitate data accountability and tracking, considering both GDPR constraints and the need for transparency in personal data handling.

The core proposition advanced by the authors is the utilization of blockchain-based smart contracts to secure data accountability and provenance tracking. The blockchain solution envisioned is built upon the Ethereum Virtual Machine (EVM), leveraging its smart contract capabilities to create publicly verifiable data usage agreements. The researchers present three distinct models of implementation, each varying in contractual granularity and scalability:

1. Subject-Specific Contracts for Each Controller: This model involves creating dedicated contracts for each data subject-controller relationship, adding a layer of specificity and granularity in data usage control.
2. Data-Centric Subject Contracts: Under this framework, a single contract covers multiple controllers but focuses on specific data types, aggregating consent for data handling in a broader manner.
3. Controller-Deployed Contracts for Aggregate Subjects: This model centralizes contract management at the controller level, permitting subjects to opt into predefined data usage policies.

The first model stands out in its ability to provide detailed tracking and accountability, catering to cases where data sensitivity is high, such as healthcare information. The third model optimizes scalability and transaction throughput by allowing controllers to manage a single contract for many subjects, which is more suited for high-volume data environments.

A significant portion of the research is devoted to addressing the enforceability of data policies encoded within blockchain-based smart contracts. The paper elucidates on encoding policies using a structured policy language, particularly focusing on preventive mechanisms to enable real-time verification of data usage against predefined terms. The authors propose hashing techniques to protect data and policy information, ensuring privacy even as data transactions become public on the blockchain.

From a technical perspective, the feasibility paper conducted illustrates the computational costs associated with various blockchain operations, providing a benchmark for gas usage in Ethereum. The paper finds that while individualized contracts offer precision in policy enforcement, they incur higher costs and demand more from blockchain resources. Conversely, aggregate contracts tend toward lower operational costs but may limit regulatory compliance details visibility.

This investigation offers critical insights into the implications of employing blockchain for data accountability. Practically, it empowers data subjects with verifiable control over their personal data's distribution and utilization by controllers and processors. Theoretically, it creates a robust framework for exploring blockchain's role in regulatory technologies (RegTech) solutions.

Predictions for future AI developments suggest that smart contracts and other blockchain innovations will continue to evolve, driving efficiencies in legal, compliance, and data management sectors. The extensibility of this approach presents opportunities for integration into broader digital identity and data rights management initiatives.

In conclusion, the paper provides a pivotal reference point in understanding how blockchain can be harnessed to meet modern data protection demands, posing pertinent questions on scaling decentralized solutions and optimizing their alignment with regulatory frameworks. Further research is warranted to enhance these models' scalability and ensure alignment with evolving data protection landscapes, potentially through advanced consensus protocols or hybrid blockchain architectures.