RT Journal Article
T1 Establishing trust in online advertising with signed transactions
A1 Pastor Valles, Antonio Ángel
A1 Cuevas Rumín, Rubén
A1 Cuevas Rumín, Ángel
A1 Azcorra Saloña, Arturo
AB Programmatic advertising operates one of the most sophisticated and efficient service platforms on the Internet. However, the complexity of this ecosystem is a direct cause of one of the most important problems in online advertising, the lack of transparency. This lack of transparency enables subsequent problems such as advertising fraud, which causes billions of dollars in losses. In this paper we propose Ads.chain, a technological solution to the lack-of-transparency problem in programmatic advertising. Ads.chain extends the current effort of the Internet Advertising Bureau (IAB) in providing traceability in online advertising through the Ads.txt and Ads.cert solutions, addressing the limitations of these techniques. Ads.chain is (to the best of the authors' knowledge) the first solution that provides end-to-end cryptographic traceability at the ad transaction level. It is a communication protocol that can be seamlessly embedded into ad-tags and the OpenRTB protocol, the de-facto standards for communications in online advertising, allowing an incremental adoption by the industry. We have implemented Ads.chain and made the code publicly available. We assess the performance of Ads.chain through a thorough analysis in a lab environment that emulates a real ad delivery process at real-life throughputs. The obtained results show that Ads.chain can be implemented with limited impact on the hardware resources and marginal delay increments at the publishers lower than 0.20 milliseconds per ad space on webpages and 2.6 milliseconds at the programmatic advertising platforms. These results confirm that Ads.chain's impact on the user experience and the overall operation of the programmatic ad delivery process can be considered negligible.
PB IEEE
SN 2169-3536
YR 2020
FD 2020-12-24
LK https://hdl.handle.net/10016/33836
UL https://hdl.handle.net/10016/33836
LA eng
NO The research leading to these results has received funding from: the European Union's Horizon 2020 innovation action programme under grant agreement No 871370 (PIMCITY project) and grant agreement 78674 (SMOOTH Project); the Ministerio de Economía, Industria y Competitividad, Spain, and the European Social Fund (EU), under the Ramón y Cajal programme (grant RyC-2015-17732), project TEC2016-76795-C6-3-R, and the FPI grant BES-2017-080053; and the TAPTAP Digital-UC3M Chair in Advanced AI and Data Science applied to Advertising and Marketing.
DS e-Archivo
RD 22 may. 2024