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Keywords :
Auction; Big data; Blockchain; Data pricing; Off-chaining; Zero-knowledge proof; Anti collusions; Auctions mechanisms; Block-chain; Privacy preserving; Semistructured data; Unstructured data; Zero-knowledge proofs; Theoretical Computer Science; Software; Information Systems; Hardware and Architecture
Abstract :
[en] Big data refers to sets of structured, semi-structured, and unstructured data collected by organizations and may be difficult to process using traditional processing methods. Big data pricing is challenging due to uncertainty about its value. Auctions are effective strategies for allocating goods to the bidder with the highest valuation and a mechanism for protecting the interests of both data sellers and market participants. However, most existing data auctions are centralized, making it difficult to establish trust and transparency among sellers, buyers, and auctioneers. Moreover, online environments suffer from the lack of transparency and verifiability, which can lead to collusion attacks in data auctions. To address these challenges, we leverage blockchain technology and propose an anti-collusion smart contract-based data auction system. Since blockchain data transparency often compromises privacy, we leverage cryptographic techniques to enhance privacy, integrity, fairness, correctness, and non-repudiation. To ensure that all participants benefit from the auction, an auction model that considers rationality and budget balance is developed. The Ethereum blockchain is used to demonstrate a proof-of-concept implementation. Analysis has shown that the approach could meet efficiency, security, and privacy requirements.
Keshavarz Kalhori, Ghazaleh; School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran
Mirzakhani, Sheyda; School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran
Akhaee, Mohammad Ali; School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran
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