Decentralized Inverse Transparency with Blockchain

Author:

Zieglmeier Valentin1ORCID,Loyola Daiqui Gabriel1ORCID,Pretschner Alexander1ORCID

Affiliation:

1. Technical University of Munich, Germany

Abstract

Employee data can be used to facilitate work, but their misusage may pose risks for individuals. Inverse transparency therefore aims to track all usages of personal data, allowing individuals to monitor them to ensure accountability for potential misusage. This necessitates a trusted log to establish an agreed-upon and non-repudiable timeline of events. The unique properties of blockchain facilitate this by providing immutability and availability. For power asymmetric environments such as the workplace, permissionless blockchain is especially beneficial as no trusted third party is required. Yet, two issues remain: (1) In a decentralized environment, no arbiter can facilitate and attest to data exchanges. Simple peer-to-peer sharing of data, conversely, lacks the required non-repudiation. (2) With data governed by privacy legislation such as the GDPR, the core advantage of immutability becomes a liability. After a rightful request, an individual’s personal data need to be rectified or deleted, which is impossible in an immutable blockchain. To solve these issues, we present Kovacs , a decentralized data exchange and usage logging system for inverse transparency built on blockchain. Its new-usage protocol ensures non-repudiation, and therefore accountability, for inverse transparency. Its one-time pseudonym generation algorithm guarantees unlinkability and enables proof of ownership, which allows data subjects to exercise their legal rights regarding their personal data. With our implementation, we show the viability of our solution. The decentralized communication impacts performance and scalability, but exchange duration and storage size are still reasonable. More importantly, the provided information security meets high requirements. We conclude that Kovacs realizes decentralized inverse transparency through secure and GDPR-compliant use of permissionless blockchain.

Funder

German Federal Ministry of Education and Research

Publisher

Association for Computing Machinery (ACM)

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