11,246 research outputs found
What Do Our Choices Say About Our Preferences?
Taking online decisions is a part of everyday life. Think of buying a house,
parking a car or taking part in an auction. We often take those decisions
publicly, which may breach our privacy - a party observing our choices may
learn a lot about our preferences. In this paper we investigate the online
stopping algorithms from the privacy preserving perspective, using a
mathematically rigorous differential privacy notion.
In differentially private algorithms there is usually an issue of balancing
the privacy and utility. In this regime, in most cases, having both optimality
and high level of privacy at the same time is impossible. We propose a natural
mechanism to achieve a controllable trade-off, quantified by a parameter,
between the accuracy of the online algorithm and its privacy. Depending on the
parameter, our mechanism can be optimal with weaker differential privacy or
suboptimal, yet more privacy-preserving. We conduct a detailed accuracy and
privacy analysis of our mechanism applied to the optimal algorithm for the
classical secretary problem. Thereby the classical notions from two distinct
areas - optimal stopping and differential privacy - meet for the first time.Comment: 22 pages, 6 figure
Enabling Privacy-preserving Auctions in Big Data
We study how to enable auctions in the big data context to solve many
upcoming data-based decision problems in the near future. We consider the
characteristics of the big data including, but not limited to, velocity,
volume, variety, and veracity, and we believe any auction mechanism design in
the future should take the following factors into consideration: 1) generality
(variety); 2) efficiency and scalability (velocity and volume); 3) truthfulness
and verifiability (veracity). In this paper, we propose a privacy-preserving
construction for auction mechanism design in the big data, which prevents
adversaries from learning unnecessary information except those implied in the
valid output of the auction. More specifically, we considered one of the most
general form of the auction (to deal with the variety), and greatly improved
the the efficiency and scalability by approximating the NP-hard problems and
avoiding the design based on garbled circuits (to deal with velocity and
volume), and finally prevented stakeholders from lying to each other for their
own benefit (to deal with the veracity). We achieve these by introducing a
novel privacy-preserving winner determination algorithm and a novel payment
mechanism. Additionally, we further employ a blind signature scheme as a
building block to let bidders verify the authenticity of their payment reported
by the auctioneer. The comparison with peer work shows that we improve the
asymptotic performance of peer works' overhead from the exponential growth to a
linear growth and from linear growth to a logarithmic growth, which greatly
improves the scalability
Trustee: Full Privacy Preserving Vickrey Auction on top of Ethereum
The wide deployment of tokens for digital assets on top of Ethereum implies
the need for powerful trading platforms. Vickrey auctions have been known to
determine the real market price of items as bidders are motivated to submit
their own monetary valuations without leaking their information to the
competitors. Recent constructions have utilized various cryptographic protocols
such as ZKP and MPC, however, these approaches either are partially
privacy-preserving or require complex computations with several rounds. In this
paper, we overcome these limits by presenting Trustee as a Vickrey auction on
Ethereum which fully preserves bids' privacy at relatively much lower fees.
Trustee consists of three components: a front-end smart contract deployed on
Ethereum, an Intel SGX enclave, and a relay to redirect messages between them.
Initially, the enclave generates an Ethereum account and ECDH key-pair.
Subsequently, the relay publishes the account's address and ECDH public key on
the smart contract. As a prerequisite, bidders are encouraged to verify the
authenticity and security of Trustee by using the SGX remote attestation
service. To participate in the auction, bidders utilize the ECDH public key to
encrypt their bids and submit them to the smart contract. Once the bidding
interval is closed, the relay retrieves the encrypted bids and feeds them to
the enclave that autonomously generates a signed transaction indicating the
auction winner. Finally, the relay submits the transaction to the smart
contract which verifies the transaction's authenticity and the parameters'
consistency before accepting the claimed auction winner. As part of our
contributions, we have made a prototype for Trustee available on Github for the
community to review and inspect it. Additionally, we analyze the security
features of Trustee and report on the transactions' gas cost incurred on
Trustee smart contract.Comment: Presented at Financial Cryptography and Data Security 2019, 3rd
Workshop on Trusted Smart Contract
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