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Exploring the dynamics of search advertiser fraud

Authors:

Geoffrey M. Voelker,

Alex C. SnoerenAuthors Info & Claims

IMC '17: Proceedings of the 2017 Internet Measurement Conference

Pages 157 - 170

https://doi.org/10.1145/3131365.3131393

Published: 01 November 2017 Publication History

Abstract

Most search engines generate significant revenue through search advertising, wherein advertisements are served alongside traditional search results. These advertisements are attractive to advertisers because ads can be targeted and prominently presented to users at the exact moment that the user is searching for relevant topics.

Deceptive advertising is harmful to all legitimate actors in the search ad ecosystem: Users are less likely to find what they are looking for and may lose trust in ads or the search engine, advertisers lose potential revenue and face unfair competition from advertisers who are not playing by the rules, and the search engine's ecosystem suffers when both users and advertisers are unhappy.

This paper explores search advertiser fraud on Microsoft's Bing search engine platform. We characterize three areas: the scale of search advertiser fraud, the targeting and bidding behavior of fraudulent advertisers, and how fraudulent advertisers impact other advertisers in the ecosystem.

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Cited By

Du SZhao MHua JZhang HChen XQian ZZhong S(2022)Who Moves My App Promotion Investment? A Systematic Study About App Distribution FraudIEEE Transactions on Dependable and Secure Computing10.1109/TDSC.2021.306820919:4(2648-2664)Online publication date: 1-Jul-2022
https://doi.org/10.1109/TDSC.2021.3068209
Griesbaum J(2022)InformationskompetenzKompetenzmodelle für den Digitalen Wandel10.1007/978-3-662-63673-2_4(67-98)Online publication date: 25-Mar-2022
https://doi.org/10.1007/978-3-662-63673-2_4
Sadeghpour SVlajic N(2021)Ads and Fraud: A Comprehensive Survey of Fraud in Online AdvertisingJournal of Cybersecurity and Privacy10.3390/jcp10400391:4(804-832)Online publication date: 16-Dec-2021
https://doi.org/10.3390/jcp1040039
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Exploring the dynamics of search advertiser fraud

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Published In

cover image ACM Conferences

IMC '17: Proceedings of the 2017 Internet Measurement Conference

November 2017

509 pages

ISBN:9781450351188

DOI:10.1145/3131365

General Chairs:
Steve Uhlig
Queen Mary University of London
,
Olaf Maennel
Tallinn University of Technology

Copyright © 2017 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Published: 01 November 2017

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UCSD Center for Networked Systems
National Science Foundation

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IMC '17

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IMC '17: Internet Measurement Conference

November 1 - 3, 2017

London, United Kingdom

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Overall Acceptance Rate 277 of 1,083 submissions, 26%

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Cited By

Du SZhao MHua JZhang HChen XQian ZZhong S(2022)Who Moves My App Promotion Investment? A Systematic Study About App Distribution FraudIEEE Transactions on Dependable and Secure Computing10.1109/TDSC.2021.306820919:4(2648-2664)Online publication date: 1-Jul-2022
https://doi.org/10.1109/TDSC.2021.3068209
Griesbaum J(2022)InformationskompetenzKompetenzmodelle für den Digitalen Wandel10.1007/978-3-662-63673-2_4(67-98)Online publication date: 25-Mar-2022
https://doi.org/10.1007/978-3-662-63673-2_4
Sadeghpour SVlajic N(2021)Ads and Fraud: A Comprehensive Survey of Fraud in Online AdvertisingJournal of Cybersecurity and Privacy10.3390/jcp10400391:4(804-832)Online publication date: 16-Dec-2021
https://doi.org/10.3390/jcp1040039
Hernandez NRecabarren RCarbunar BAhmed SLevin DMislove AAmann JLuckie M(2021)RacketStoreProceedings of the 21st ACM Internet Measurement Conference10.1145/3487552.3487837(639-657)Online publication date: 2-Nov-2021
https://dl.acm.org/doi/10.1145/3487552.3487837
Yang DLi ZWang XSalamatian KXie G(2021)Exploiting the Community Structure of Fraudulent Keywords for Fraud Detection in Web SearchJournal of Computer Science and Technology10.1007/s11390-021-0218-236:5(1167-1183)Online publication date: 30-Sep-2021
https://doi.org/10.1007/s11390-021-0218-2
Ma WXu H(2021)A Study of the Partnership Between Advertisers and PublishersPassive and Active Measurement10.1007/978-3-030-72582-2_33(564-580)Online publication date: 30-Mar-2021
https://doi.org/10.1007/978-3-030-72582-2_33
Bermudez-Villalva AMusolesi MStringhini G(2020)A Measurement Study on the Advertisements Displayed to Web Users Coming from the Regular Web and from Tor2020 IEEE European Symposium on Security and Privacy Workshops (EuroS&PW)10.1109/EuroSPW51379.2020.00072(494-499)Online publication date: Sep-2020
https://doi.org/10.1109/EuroSPW51379.2020.00072
Liu BLiu ZZong PLu CDuan HLiu YAlrwais SWang XHao SJia YZhang YChen KZhang Z(2019)TraffickStop: Detecting and Measuring Illicit Traffic Monetization Through Large-Scale DNS Analysis2019 IEEE European Symposium on Security and Privacy (EuroS&P)10.1109/EuroSP.2019.00047(560-575)Online publication date: Jun-2019
https://doi.org/10.1109/EuroSP.2019.00047
Srinivasan BKountouras AMiramirkhani NAlam MNikiforakis NAntonakakis MAhamad MChampin PGandon FMédini LLalmas MIpeirotis P(2018)Exposing Search and Advertisement Abuse Tactics and Infrastructure of Technical Support ScammersProceedings of the 2018 World Wide Web Conference10.1145/3178876.3186098(319-328)Online publication date: 10-Apr-2018
https://dl.acm.org/doi/10.1145/3178876.3186098

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