Differentially private and strategy-proof spectrum auction with approximate revenue maximization

The rapid growth of wireless mobile users and applications has led to high demand of spectrum. Auction is a powerful tool to improve the utilization of spectrum resource, and many auction mechanisms have been proposed thus far. However, none of them has considered both the privacy of bidders and the revenue gain of the auctioneer together. In this paper, we study the design of privacy-preserving auction mechanisms. We first propose a differentially private auction mechanism which can achieve strategy-proofness and a near optimal expected revenue based on the concept of virtual valuation. Assuming the knowledge of the bidders' valuation distributions, the near optimal differentially private and strategy-proof auction mechanism uses the generalized Vickrey-Clarke-Groves auction payment scheme to achieve high revenue with a high probability. To tackle its high computational complexity, we also propose an approximate differentially PrivAte, Strategy-proof, and polynomially tractable Spectrum (PASS) auction mechanism that can achieve a suboptimal revenue. PASS uses a monotone allocation algorithm and the critical payment scheme to achieve strategy-proofness. We also evaluate PASS extensively via simulation, showing that it can generate more revenue than existing mechanisms in the spectrum auction markets.