Abstract Ad exchanges are kind of the most popular online advertising marketplaces for trading ad spaces over the Internet. Ad exchanges run auctions to sell diverse ad spaces on the publishers’ web-pages to advertisers, who want to display ads on ad spaces. However, the parties in an ad auction cannot verify whether the auction is carried out correctly or not. Furthermore, the advertisers are usually unwilling to reveal their sensitive bids and identities. In this paper, we jointly consider the auction verifiability and the advertisers’ privacy preservation, and thus propose ERA, which is an E fficient, p R ivacy-preserving, and verifi A ble online auction mechanism for ad exchanges. ERA exploits an order preserving encryption scheme to guarantee privacy preservation, and achieves verifiability by constructing a novel protocol of privacy preserving integer comparison, which is built on the Paillier homomorphic encryption scheme. We extensively evaluate the performance of ERA, and our evaluation results show that ERA satisfies several desirable properties with low computation, communication, and storage overheads, so ERA can be easily deployed in today's ad exchanges.
Inspired by early works @cite_10 @cite_32 , various privacy preserving and verifiable auction mechanisms have been extensively studied. The existing works generally fall into the following three categories with different auction models.
@cite_10 @cite_32
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We study the role that privacy-preserving algorithms, which prevent the leakage of specific information about participants, can play in the design of mechanisms for strategic agents, which must encourage players to honestly report information. Specifically, we show that the recent notion of differential privacv, in addition to its own intrinsic virtue, can ensure that participants have limited effect on the outcome of the mechanism, and as a consequence have limited incentive to lie. More precisely, mechanisms with differential privacy are approximate dominant strategy under arbitrary player utility functions, are automatically resilient to coalitions, and easily allow repeatability. We study several special cases of the unlimited supply auction problem, providing new results for digital goods auctions, attribute auctions, and auctions with arbitrary structural constraints on the prices. As an important prelude to developing a privacy-preserving auction mechanism, we introduce and study a generalization of previous privacy work that accommodates the high sensitivity of the auction setting, where a single participant may dramatically alter the optimal fixed price, and a slight change in the offered price may take the revenue from optimal to zero. Describes a novel Internet auction model achieving verifiable fairness, a requirement aimed at enhancing the trust of bidders in auctioneers. Distrust in remote auctioneers prevents bidders from participating in Internet auctioning. According to proposed survey reports, this study presents four characteristics that render the Internet untrustworthy for bidders. These intrinsic properties suggest that auction sites not only follow auction policies, but provide customers with evidence validating that the policies are applied fairly. Evidence of verifiable fairness provides bidders with a basis for confidence in Internet auctions. Cryptographic techniques are also applied herein to establish a novel auction model with evidence to manifest and verify every step of the auctioneer. Analysis results demonstrate that the proposed model satisfies various requirements regarding fairness and privacy. Moreover, in the proposed model, the losing bids remain sealed. We investigate whether it is possible to preserve privacy in sealed-bid auctions to a maximal extent. In particular, this paper focuses on unconditional full privacy , i.e., privacy that relies neither on trusted third parties (like auctioneers), nor on computational intractability assumptions (like the hardness of factoring). These constraints imply a scenario in which bidders exchange messages according to some predefined protocol in order to jointly determine the auction outcome without revealing any additional information. It turns out that the first-price sealed-bid auction can be emulated by an unconditionally fully private protocol. However, the protocol's round complexity is exponential in the bid size, and there is no more efficient protocol. On the other hand, we prove the impossibility of privately emulating the second-price sealed-bid auction for more than two bidders. This impossibility holds even when relaxing various privacy constraints such as allowing the revelation of all but one losing bid (while maintaining anonymity) or allowing the revelation of the second highest bidder's identity. Privacy has become a factor of increasing importance in auction design. We propose general techniques for cryptographic first-price and (M+1)st-price auction protocols that only yield the winners' identities and the selling price. Moreover, if desired, losing bidders learn no information at all, except that they lost. Our security model is merely based on computational intractability. In particular, our approach does not rely on trusted third parties, e.g., auctioneers. We present an efficient implementation of the proposed techniques based on El Gamal encryption whose security only relies on the intractability of the decisional Diffie—Hellman problem. The resulting protocols require just three rounds of bidder broadcasting in the random oracle model. Communication complexity is linear in the number of possible bids.