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Bridging the Privacy Gap: Enhanced User Consent Mechanisms on the Web
Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.ORCID iD: 0009-0005-9031-6600
Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering. Sectra Communications, Sweden.ORCID iD: 0000-0002-7631-0625
Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0003-1367-1594
2023 (English)In: Proc. NDSS Workshop on Measurements, Attacks, and Defenses for the Web (MADWeb @NDSS), 2023Conference paper, Published paper (Refereed)
Abstract [en]

In the age of the General Data Protection Regula-tion (GDPR) and the California Consumer Privacy Act (CCPA),privacy and consent control have become even more apparent forevery-day web users. Privacy banners in all shapes and sizes askfor permission through more or less challenging designs and makeprivacy control more of a struggle than they help users’ privacy.In this paper, we present a novel solution expanding the AdvancedData Protection Control (ADPC) mechanism to bridge currentgaps in user data and privacy control. Our solution moves theconsent control to the browser interface to give users a seamlessand hassle-free experience, while at the same time offering contentproviders a way to be legally compliant with legislation. Throughan extensive review, we evaluate previous works and identifycurrent gaps in user data control. We then present a blueprintfor future implementation and suggest features to support privacycontrol online for users globally. Given browser support, thesolution provides a tangible path to effectively achieve legallycompliant privacy and consent control in a user-oriented mannerthat could allow them to again browse the web seamlessly.

Place, publisher, year, edition, pages
2023.
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:liu:diva-199090DOI: 10.14722/madweb.2023.23017ISBN: 1891562878 (print)OAI: oai:DiVA.org:liu-199090DiVA, id: diva2:1811234
Conference
Workshop on Measurements, Attacks, and Defenses for the Web (MADWeb) 2023, San Diego, CA, USA, 3 March, 2023
Note

Best paper runner-up award

Available from: 2023-11-11 Created: 2023-11-11 Last updated: 2023-11-16Bibliographically approved

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Bruhner, Carl MagnusHasselquist, DavidCarlsson, Niklas

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