Cryptology ePrint Archive: Report 2021/727

SoK: Privacy-Preserving Computing in the Blockchain Era

Ghada Almashaqbeh and Ravital Solomon

Abstract: Cryptocurrency and blockchain continue to build on an innovative computation model that has paved the way for a large variety of applications. However, privacy is a huge concern as most (permissionless) blockchains log everything in the clear. This has resulted in several academic and industrial initiatives to address privacy. Starting with the UTXO model introduced by Bitcoin, initial works brought confidentiality and anonymity to payments. Recent works have expanded to support more generalized forms of private computation. Such solutions tend to be highly involved as they rely on advanced cryptographic primitives and creative techniques to handle issues related to dealing with private blockchain records (e.g. concurrency, private coin tracking to prevent double spending, efficiency). This situation makes it hard to comprehend the current state-of-the-art, much less build on top of it.

To address these challenges, we provide a systematization of knowledge for privacy-preserving solutions in blockchain. To the best of our knowledge, our work is the first of its kind. After motivating design challenges, we provide an overview of the zero-knowledge proof systems used in supporting blockchain privacy, focusing on their key features and limitations. Then, we develop a systematization of knowledge framework using which we group the state-of-the-art privacy preserving solutions under three categories: private payments, computation with input/output privacy, and function privacy. We briefly touch upon challenges and implications including misuse, regulations and compliance, usability, and limited functionality. Our work seeks to highlight open problems and research questions to guide future work directions.

Category / Keywords: cryptographic protocols / Blockchains; private payments, privacy-preserving computing; smart contracts; zero knowledge proofs; homomorphic encryption

Date: received 31 May 2021

Contact author: ghada almashaqbeh at uconn edu,ravital@nucypher com

Available format(s): PDF | BibTeX Citation

Version: 20210602:115058 (All versions of this report)

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