$K$-anonymous Signaling Scheme
Binyi Chen, Tao Qin, Tie-Yan Liu
TL;DR
This paper introduces a $K$-anonymous signaling scheme for ad auctions that enhances welfare and revenue while safeguarding user privacy, providing theoretical hardness results and approximation algorithms.
Contribution
It proposes a novel $K$-anonymous signaling scheme for ad auctions, analyzes its computational hardness, and develops algorithms for near-optimal welfare and revenue.
Findings
Hardness results for welfare and revenue maximization
Approximation algorithms for the signaling scheme
Improved welfare and revenue with privacy protection
Abstract
We incorporate signaling scheme into Ad Auction setting, to achieve better welfare and revenue while protect users' privacy. We propose a new \emph{-anonymous signaling scheme setting}, prove the hardness of the corresponding welfare/revenue maximization problem, and finally propose the algorithms to approximate the optimal revenue or welfare.
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Taxonomy
TopicsAuction Theory and Applications · Cryptography and Data Security · Internet Traffic Analysis and Secure E-voting