Secure Multi-Party Computation on Blockchain: An Overview

Zhong, Hanrui; Sang, Yingpeng; Zhang, Yongchun; Xi, Zhicheng

doi:10.1007/978-981-15-2767-8_40

Cited by 24 publications

(9 citation statements)

References 16 publications

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“…Moreover, unlike MPC, which uses encryption, differential privacy protects the data by adding random noise during the analysis. Nevertheless, those technologies can complement each other to implement robust security requirements in various use cases (e.g., Alter et al, 2018;Pettai & Laud, 2015;Zhong et al, 2020).…”

Section: Multi-party Computation (Mpc)mentioning

confidence: 99%

It is not (only) about privacy: How multi-party computation redefines control, trust, and risk in data sharing

2022

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Firms are often reluctant to share data because of mistrust, concerns over control, and other risks. Multi-party computation (MPC) is a new technique to compute meaningful insights without having to transfer data. This paper investigates if MPC affects known antecedents for data sharing decisions: control, trust, and risks. Through 23 qualitative interviews in the automotive industry, we find that MPC (1) enables new ways of technology-based control, (2) reduces the need for inter-organizational trust, and (3) prevents losing competitive advantage due to data leakage. However, MPC also creates the need to trust technology and introduces new risks of data misuse. These impacts arise if firms perceive benefits from sharing data, have high organizational readiness, and perceive data as non-sensitive. Our findings show that known antecedents of data sharing should be specified differently with MPC in place. Furthermore, we suggest reframing MPC as a data collaboration technology beyond enhancing privacy.

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Section: Multi-party Computation (Mpc)mentioning

confidence: 99%

It is not (only) about privacy: How multi-party computation redefines control, trust, and risk in data sharing

2022

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“…Throughout MPC's short history, most implementations have been realized using at least one of the following four concepts (Zhong et al, 2019):…”

Section: Multi-party Computationmentioning

confidence: 99%

Analysis and Application of Verifiable Computation Techniques in Blockchain Systems for the Energy Sector

Zeiselmair¹,

Steinkopf²,

Gallersdörfer³

et al. 2021

Front. Blockchain

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The energy system is becoming increasingly decentralized. This development requires integrating and coordinating a rising number of actors and small units in a complex system. Blockchain could provide a base infrastructure for new tools and platforms that address these tasks in various aspects—ranging from dispatch optimization or dynamic load adaption to (local) market mechanisms. Many of these applications are currently in development and subject to research projects. In decentralized energy markets especially, the optimized allocation of energy products demands complex computation. Combining these with distributed ledger technologies leads to bottlenecks and challenges regarding privacy requirements and performance due to limited storage and computational resources. Verifiable computation techniques promise a solution to these issues. This paper presents an overview of verifiable computation technologies, including trusted oracles, zkSNARKs, and multi-party computation. We further analyze their application in blockchain environments with a focus on energy-related applications. Applied to a distinct optimization problem of renewable energy certificates, we have evaluated these solution approaches and finally demonstrate an implementation of a Simplex-Optimization using zkSNARKs as a case study. We conclude with an assessment of the applicability of the described verifiable computation techniques and address limitations for large-scale deployment, followed by an outlook on current development trends.

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“…Based on our results, the use of cryptographic protocols for privacy-preserving analysis and computation is limited in current blockchain-based approaches in genomics. Cryptographic protocols such as Multi-Party Computation (MPC) can enhance privacy and when combined with blockchain and smart contracts, it can help address the security, trust, and verifiability issues in distributed analytics [138]. Current research in this field has shown the feasibility of performing distributed privacy-preserving analysis on blockchain [51,139].…”

Section: Future Directionsmentioning

confidence: 99%

Blockchain for Genomics: A Systematic Literature Review

Alghazwi,

Turkmen,

van der Velde

et al. 2021

Preprint

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Human genomic data carry unique information about an individual and offer unprecedented opportunities for healthcare. The clinical interpretations derived from large genomic datasets can greatly improve healthcare and pave the way for personalized medicine.Sharing genomic datasets, however, pose major challenges, as genomic data is different from traditional medical data, indirectly revealing information about descendants and relatives of the data owner and carrying valid information even after the owner passes away. Therefore, stringent data ownership and control measures are required when dealing with genomic data. In order to provide secure and accountable infrastructure, blockchain technologies offer a promising alternative to traditional distributed systems. Indeed, the research on blockchain-based infrastructures tailored to genomics is on the rise. However, there is a lack of a comprehensive literature review that summarizes the current state-of-the-art methods in the applications of blockchain in genomics. In this paper, we systematically look at the existing work both commercial and academic, and discuss the major opportunities and challenges. Our study is driven by five research questions that we aim to answer in our review. We also present our projections of future research directions which we hope the researchers interested in the area can benefit from.

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Secure Multi-Party Computation on Blockchain: An Overview

Cited by 24 publications

References 16 publications

It is not (only) about privacy: How multi-party computation redefines control, trust, and risk in data sharing

It is not (only) about privacy: How multi-party computation redefines control, trust, and risk in data sharing

Analysis and Application of Verifiable Computation Techniques in Blockchain Systems for the Energy Sector

Blockchain for Genomics: A Systematic Literature Review

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