ERA: Towards privacy preservation and verifiability for online ad exchanges

Abstract

Ad exchanges are kind of the most popular online advertising marketplaces for trading ad spaces over the Internet. Ad exchanges run auctions to sell diverse ad spaces on the publishers' web-pages to advertisers, who want to display ads on ad spaces. However, the parties in an ad auction cannot verify whether the auction is carried out correctly or not. Furthermore, the advertisers are usually unwilling to reveal their sensitive bids and identities. In this paper, we jointly consider the auction verifiability and the advertisers' privacy preservation, and thus propose ERA, which is an Efficient, pRivacy-preserving, and verifiAble online auction mechanism for ad exchanges. ERA exploits an order preserving encryption scheme to guarantee privacy preservation, and achieves verifiability by constructing a novel protocol of privacy preserving integer comparison, which is built on the Paillier homomorphic encryption scheme. We extensively evaluate the performance of ERA, and our evaluation results show that ERA satisfies several desirable properties with low computation, communication, and storage overheads, so ERA can be easily deployed in today's ad exchanges.

Achieving Data Truthfulness and Privacy Preservation in Data Markets

“…The registration center maintains an online database of registrations, and assigns each registered data contributor an identity and a password to activate the tamper-proof device. Besides, she maintains an official website, called certificated bulletin board [18], [19], on which the legitimate system participants can publish essential information, e.g., whitelists, blacklists, resubmit-lists, and reward-lists of data contributors. Yet, another duty of the registration center is to set up the parameters for a signature scheme and a cryptosystem.…”

The Digital Advertising Ecosystem Visualization – Literature Review

“…Research report the time component differently: From the advertising request due to the HTML request of a user on supply side to the delivery of the ad, their opinions differ. Latter go from less than 100ms (Yuan, 2015;Chaudhuri, Bagherjeiran and Liu, 2017;Papadopoulos et al, 2017;Parssinen et al, 2018) to around 100ms (Chen et al, 2017;Niu et al, 2017;Iordanou et al, 2018), to longer than 100ms Kanguri, 2016, 2017;Kumar, 2017).…”

Online Advertising Security: Issues, Taxonomy, and Future Directions

“…Following this, the publisher asks the ad exchange to fetch the ad that best matches the user's profile and has the best price (step 3). The ad exchange starts an auction between multiple advertisers to determine which can make the most profit for the publisher and consequently for the whole network [33] (step 4). Finally, the highest paying advertiser (winning bidder) wins the auction (step 5) and its ad is served and displayed to the user (steps 6-7).…”