2 research outputs found
VCG Under Sybil (False-name) Attacks -- a Bayesian Analysis
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.Comment: This is an extended version of an article to appear in AAAI-2020.
Supporting code for generating the article's figures can be found at
https://github.com/yotam-gafni/vcg_bayesian_fn