Hugo Jonker (Open University Netherlands), Stefan Karsch (TH Koln), Benjamin Krumnow (TH Koln), Godfried Meesters (Open University Netherlands)

Online vendors typically offer different stores to sell their items, such as desktop site, mobile site, country-specific sites, etc. Online rumours and news media reports persist that item prices between such views differ. While several academic works have investigated price differentiation, to date, no systematic method for analysing this question was put forth. We devise an approach to investigate such store-based price differentiation, based on three pillars: a framework that can perform cross-store data acquisition synchronously, a method to perform cross-store item matching, and constraints to limit client-side noise factors. We test our method in an initial case study to investigate store effects on flight pricing. We gather pricing data of 824 flights from 15 stores (incl. desktop sites, mobile apps, and mobile sites) over a 38-day period. Our experiment shows that price differences occur frequently. Moreover, even in a limited run we find strong indications of store-specific pricing for certain vendors. We conclude that (i) a larger study into store-based price differentiation is needed to better gauge this effect; (ii) future research in this general domain should take store-based differences into account in their study design.

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Harjasleen Malvai (UIUC/IC3), Lefteris Kokoris-Kogias (IST Austria), Alberto Sonnino (Mysten Labs), Esha Ghosh (Microsoft Research), Ercan Oztürk (Meta), Kevin Lewi (Meta), Sean Lawlor (Meta)

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NinjaDoH: A Censorship-Resistant Moving Target DoH Server Using Hyperscalers...

Scott Seidenberger (University of Oklahoma), Marc Beret (University of Oklahoma), Raveen Wijewickrama (University of Texas at San Antonio), Murtuza Jadliwala (University of Texas at San Antonio), Anindya Maiti (University of Oklahoma)

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Theodor Schnitzler (Research Center Trustworthy Data Science and Security, TU Dortmund, and Ruhr-Universität Bochum)

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