Graph Ranking and the Cost of Sybil Defense

Gwendolyn Farach-Colton, Martin Farach-Colton, Leslie Ann Goldberg, Hanna Komlos, John Lapinskas, Reut Levi, Moti Medina, Miguel A. Mosteiro

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Ranking functions such as PageRank assign numeric values (ranks) to nodes of graphs, most notably the web graph. Node rankings are an integral part of Internet search algorithms, since they can be used to order the results of queries. However, these ranking functions are famously subject to attacks by spammers, who modify the web graph in order to give their own pages more rank.We characterize the interplay between rankers and spammers as a game. We define the two critical features of this game, spam resistance and distortion, based on how spammers spam and how rankers protect against spam. We observe that all the ranking functions that are well-studied in the literature, including the original formulation of PageRank, have poor spam resistance, poor distortion, or both.Finally, we study Min-PPR, the form of PageRank used at Google itself, but which has received no (theoretical or empirical) treatment in the literature. We prove that Min-PPR has low distortion and high spam resistance. A secondary benefit is that Min-PPR comes with an explicit cost function on nodes that shows how important they are to the spammer; thus a ranker can focus their spam-detection capacity on these vulnerable nodes. Both Min-PPR and its associated cost function are straightforward to compute.

Original languageEnglish
Title of host publicationEC 2023 - Proceedings of the 24th ACM Conference on Economics and Computation
PublisherAssociation for Computing Machinery, Inc
Pages586-625
Number of pages40
ISBN (Electronic)9798400701047
DOIs
StatePublished - 9 Jul 2023
Event24th ACM Conference on Economics and Computation, EC 2023 - London, United Kingdom
Duration: 9 Jul 202312 Jul 2023

Publication series

NameEC 2023 - Proceedings of the 24th ACM Conference on Economics and Computation

Conference

Conference24th ACM Conference on Economics and Computation, EC 2023
Country/TerritoryUnited Kingdom
CityLondon
Period9/07/2312/07/23

Bibliographical note

Publisher Copyright:
© 2023 ACM.

Funding

*The author was supported by NSF grants CNS 2118620 and CCF 2106999. †The author was supported by the Israel Science Foundation under Grant 1867/20. ‡The author was supported by the Israel Science Foundation under Grant 867/19. §The author was supported by Pace University SRC Award and Kenan Fund.

FundersFunder number
Pace University
National Science FoundationCNS 2118620, CCF 2106999
Israel Science Foundation1867/20, 867/19

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