A4 Vertaisarvioitu artikkeli konferenssijulkaisussa
Investigating Third-Party Data Leaks and in Online Electronics Stores
Tekijät: Heino, Timi; Carlsson, Robin; Puhtila, Panu; Rajapaksha, Sammani; Lohi, Henna; Rauti, Sampsa
Toimittaja: Yang, Xin-She; Sherratt, Simon; Dey, Nilanjan; Joshi, Amit
Konferenssin vakiintunut nimi: International Congress on Information and Communication Technology
Kustantaja: Springer Science and Business Media Deutschland GmbH
Julkaisuvuosi: 2025
Lehti: Lecture Notes in Networks and Systems
Kokoomateoksen nimi: Proceedings of Tenth International Congress on Information and Communication Technology, ICICT 2025, London, Volume 6
Vuosikerta: 1412
Aloitussivu: 383
Lopetussivu: 394
ISBN: 978-981-96-6428-3
eISBN: 978-981-96-6429-0
ISSN: 2367-3370
eISSN: 2367-3389
DOI: https://doi.org/10.1007/978-981-96-6429-0_32
Julkaisun avoimuus kirjaamishetkellä: Ei avoimesti saatavilla
Julkaisukanavan avoimuus : Ei avoin julkaisukanava
Verkko-osoite: https://link.springer.com/chapter/10.1007/978-981-96-6429-0_32
Electronics is one of the most popular product categories among consumers online. In this paper, we conduct a study on the third-party data leaks occurring in the websites of the most online electronics stores used by Finnish residents, as well as the amounts of third parties present at these websites. We studied the leaks by recording and analyzing the network traffic happening from the website while conducting actions at the website that the normal user does when purchasing the product. We also analyze dark patterns found in these websites’ cookie consent banners. Our results show that in 80% of the cases, the product name, product ID, and price were leaked to third parties along with the data identifying the user. Almost all of the inspected websites used dark patterns in their cookie consent banners, and privacy policies often had severe deficiencies in informing the user of the extent of data collection.
Julkaisussa olevat rahoitustiedot:
This research has been funded by Academy of Finland project 327397, IDA – Intimacy in Data-Driven Culture.
