Privacy-Preserving Auction for Big Data Trading Using Homomorphic Encryption
Cyber-Physical Systems (smart grid, smart transportation, smart cities, etc.), driven by advances in Internet of Things (IoT) technologies, will provide the infrastructure and integration of smart applications to accelerate the generation and collection of big data to an unprecedented scale. As now a fundamental commodity in our current information age, such big data is a crucial key to competitiveness in modern commerce. In this paper, we address the issue of privacy preservation for data auction in CPS by leveraging the concept of homomorphic cryptography and secured network protocol design. Specifically, we propose a generic Privacy-Preserving Auction Scheme (PPAS), in which the two independent entities of Auctioneer and Intermediate Platform comprise an untrusted third-party trading platform. Via the implementation of homomorphic encryption and one-time pad, a winner in the auction process can be determined and all bidding information is disguised. Yet, to further improve the security of the privacy-preserving auction, we additionally propose an Enhanced Privacy-Preserving Auction Scheme (EPPAS) that leverages an additional signature verification mechanism. The feasibilities of both schemes are validated through detailed theoretical analyses and extensive performance evaluations, including assessment of the resilience to attacks. In addition, we discuss some open issues and extensions relevant to our scheme.
The existing auction schemes, we are not only focused on the efficiency and security of the platform, but also the integration of the third-party auction platform as a new concept to satisfy the demands of big data and CPS. Through our experiments, the proposed platform has demonstrated good performance, and through the application of homomorphic encryption, all the private information is encrypted during the auction process, demonstrably protecting both owner and bidder privacy.
Basic Scheme: We propose a basic scheme denoted as the Privacy-Preserving Auction Scheme (PPAS) to enable auctions with encrypted bids. We provide a detailed description of the designed architecture and algorithms, an analysis of the auction scheme, and evaluate its performance via emulation. • Enhanced Scheme: Based on insights from our analysis of the PPAS scheme, we propose an Enhanced Privacy Preserved Auction Scheme (EPPAS), to improve the security and privacy of the auction. We provide the detailed architecture and algorithms of the improved EPPAS, analysis of the improved auction, and an additional performance evaluation and comparison. The evaluation results demonstrate the effectiveness, efficiency, and security of our proposed EPPAS. • Extension: As the proposed scheme is generic, and a variety of auction rules can be provisioned and more efficient cryptosystems can be applied, we address potential avenues of future research to meet the requirements of different data auctions.
we have addressed the issue of protecting information privacy during the data auction in the thirdparty auction platform. We have leveraged the concept of homomorphic encryption to design a Privacy-Preserving Auction Scheme (PPAS). In order to carry out a privacypreserving auction, we selected a set of crypto-primitives and designed algorithms in our system to enable the efficiency of the auction process. To further improve the security and resistance to attacks of PPAS, we proposed the Enhanced Privacy-Preserving Auction Scheme (EPPAS). The prototypical system of the auction scheme has been implemented to conduct thorough experimental evaluation. The experimental results demonstrate that our proposed scheme is capable of ensuring the determination of an auction winner with a 100 % correct rate under normal operations and without leakage of private information. In addition, multiple attack scenarios against the auction were investigated and applied in our evaluation, and have been correctly detected and prevented. We also discussed some extensions of our designed system. Our generic framework can be further integrated with other cryptosystems and auction rules to improve the performance and the scope of the data auction.
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