Crowd-assisted search for price discrimination in e-commerce: first results

After years of speculation, price discrimination in ecommerce driven by the personal information that users leave (involuntarily) online, has started attracting the attention of privacy researchers, regulators, and the press. In our previous work we demonstrated instances of products whose prices varied online depending on the location and the characteristics of prospective online buyers. In an effort to scale up our study we have turned to crowd-sourcing. Using a browser extension we have collected the prices obtained by an initial set of 340 test users as they surf the web for products of their interest. This initial dataset has permitted us to identify a set of online stores where price variation is more pronounced. We have focused on this subset, and performed a systematic crawl of their products and logged the prices obtained from different vantage points and browser configurations. By analyzing this dataset we see that there exist several retailers that return prices for the ...

• Type: Journal
• Year: 2013
• Where: CONEXT
• Authors: Jakub Mikians, László Gyarmati, Vijay Erramilli, Nikolaos Laoutaris
• Keywords: Computer Networks, CONEXT 2013