Privacy-Preserving Statistical Analysis of Health Data Using Paillier Homomorphic Encryption and Permissioned Blockchain

Ghadamyari, Mahdi; Samet, Saeed

doi:10.1109/bigdata47090.2019.9006231

Cited by 23 publications

(14 citation statements)

References 29 publications

(21 reference statements)

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“…However, their solution requires “privileged clients” that have access to the same private key peers used for data encryption. Ghadamyari et al [ 12 ] also focused on Hyperledger Fabric. Although they facilitated the Paillier cryptosystem to obtain data privacy and used access control list rules to restrict access to the ledger, data owned by different participants are encrypted by the same public key, resulting in disclosing privacy when the owner of the private key and the invoker of the smart contract conspire.…”

Section: Related Workmentioning

confidence: 99%

“…Blockchain perfectly suits secure MPC protocols because they all deal with security and trust issues in distributed environments [ 11 ]. There are many practical scenarios that benefit from utilizing secure MPC based on blockchain, such as statistical analysis of health data [ 12 ], anonymous electronic voting [ 13 ], initial public offering(IPO) [ 3 ] and edge computing [ 14 ].…”

Section: Introductionmentioning

confidence: 99%

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Using Secure Multi-Party Computation to Protect Privacy on a Permissioned Blockchain

Zhou

Feng

Wang

et al. 2021

Sensors

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The development of information technology has brought great convenience to our lives, but at the same time, the unfairness and privacy issues brought about by traditional centralized systems cannot be ignored. Blockchain is a peer-to-peer and decentralized ledger technology that has the characteristics of transparency, consistency, traceability and fairness, but it reveals private information in some scenarios. Secure multi-party computation (MPC) guarantees enhanced privacy and correctness, so many researchers have been trying to combine secure MPC with blockchain to deal with privacy and trust issues. In this paper, we used homomorphic encryption, secret sharing and zero-knowledge proofs to construct a publicly verifiable secure MPC protocol consisting of two parts—an on-chain computation phase and an off-chain preprocessing phase—and we integrated the protocol as part of the chaincode in Hyperledger Fabric to protect the privacy of transaction data. Experiments showed that our solution performed well on a permissioned blockchain. Most of the time taken to complete the protocol was spent on communication, so the performance has a great deal of room to grow.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Using Secure Multi-Party Computation to Protect Privacy on a Permissioned Blockchain

Zhou

Feng

Wang

et al. 2021

Sensors

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“…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]. Researchers can further investigate and develop new approaches for genomic applications.…”

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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“…They experimentally proved that some attacks such as collision, preimage and attack on the digital wallet can be avoided through encrypting block using Goldwasser-Micali and Paillier encryption schemes. Moreover, Paillier homomorphic encryption was used by Ghadamyari et al [40] to implement privacy-preserving data access model for private blockchains which was used to perform statistical analysis on encrypted health data stored on-chain. Similarly, She et al [82] designed an algorithm based on Paillier scheme which encrypts sensitive data of all gateway peers before uploading them to the consortium blockchain.…”

Section: Homomorphic Encryptionmentioning

confidence: 99%

Review of Techniques for Privacy-Preserving Blockchain Systems

Satybaldy

Nowostawski

2020

Proceedings of the 2nd ACM International Symposium on Blockchain and Secure Critical Infrastructure

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Privacy plays a central role in many application domains that utilize blockchain technology. It is central in Personal Data Management, Electronic Health records, or systems that interact with any public institution. However, blockchains are subject to potential privacy issues such as transaction linkability, compliance with data protection regulations, on-chain data privacy, and malicious smart contracts. To deal with these challenges, novel privacy-preserving solutions based on crypto-privacy techniques are emerging. The goal of this survey is to provide insights into the privacy-preserving techniques associated with blockchain. We analyse the existing privacypreserving mechanisms for blockchain and propose a framework that categorizes the main techniques examined. Furthermore, we summarize some typical applications of blockchain where the privacy protection is the main requirement. CCS CONCEPTS • General and reference → Surveys and overviews; Evaluation; • Security and privacy → Cryptography; Privacy-preserving protocols; Cryptanalysis and other attacks; • Software and its engineering → Peer-to-peer architectures; • Social and professional topics → Identity theft.

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Privacy-Preserving Statistical Analysis of Health Data Using Paillier Homomorphic Encryption and Permissioned Blockchain

Cited by 23 publications

References 29 publications

Using Secure Multi-Party Computation to Protect Privacy on a Permissioned Blockchain

Using Secure Multi-Party Computation to Protect Privacy on a Permissioned Blockchain

Blockchain for Genomics: A Systematic Literature Review

Review of Techniques for Privacy-Preserving Blockchain Systems

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