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arXiv · 1911.07210

VCG Under False-name Attacks: a Bayesian Analysis

Yotam Gafni·Ron Lavi·Moshe Tennenholtz
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Abstract

VCG is a classical combinatorial auction that maximizes social welfare. However, while the standard single-item Vickrey auction is false-name-proof, a major failure of multi-item VCG is its vulnerability to false-name attacks. This occurs already in the natural bare minimum model in which there are two identical items and bidders are single-minded. Previous solutions to this challenge focused on developing alternative mechanisms that compromise social welfare. We re-visit the VCG auction vulnerability and consider the bidder behavior in Bayesian settings. In service of that we introduce a novel notion, termed the granularity threshold, that characterizes VCG Bayesian resilience to false-name attacks as a function of the bidder type distribution. Using this notion we show a large class of cases in which VCG indeed obtains Bayesian resilience for the two-item single-minded setting.

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Yotam Gafni, Ron Lavi, Moshe Tennenholtz. 2019-11-17. VCG Under False-name Attacks: a Bayesian Analysis. https://arxiv.org/abs/1911.07210

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