Carl Magnus Bruhner (Linkoping University), David Hasselquist (Linkoping University, Sectra Communications), Niklas Carlsson (Linkoping University)

In the age of the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA), privacy and consent control have become even more apparent for every-day web users. Privacy banners in all shapes and sizes ask for permission through more or less challenging designs and make privacy control more of a struggle than they help users’ privacy. In this paper, we present a novel solution expanding the Advanced Data Protection Control (ADPC) mechanism to bridge current gaps in user data and privacy control. Our solution moves the consent control to the browser interface to give users a seamless and hassle-free experience, while at the same time offering content providers a way to be legally compliant with legislation. Through an extensive review, we evaluate previous works and identify current gaps in user data control. We then present a blueprint for future implementation and suggest features to support privacy control online for users globally. Given browser support, the solution provides a tangible path to effectively achieve legally compliant privacy and consent control in a user-oriented manner that could allow them to again browse the web seamlessly.

View More Papers

Lightning Community Shout-Outs to:

(1) Jonathan Petit, Secure ML Performance Benchmark (Qualcomm) (2) David Balenson, The Road to Future Automotive Research Datasets: PIVOT Project and Community Workshop (USC Information Sciences Institute) (3) Jeremy Daily, CyberX Challenge Events (Colorado State University) (4) Mert D. Pesé, DETROIT: Data Collection, Translation and Sharing for Rapid Vehicular App Development (Clemson University) (5) Ning…

Read More

Security Awareness Training through Experiencing the Adversarial Mindset

Jens Christian Dalgaard, Niek A. Janssen, Oksana Kulyuk, Carsten Schurmann (IT University of Copenhagen)

Read More

VulHawk: Cross-architecture Vulnerability Detection with Entropy-based Binary Code Search

Zhenhao Luo (College of Computer, National University of Defense Technology), Pengfei Wang (College of Computer, National University of Defense Technology), Baosheng Wang (College of Computer, National University of Defense Technology), Yong Tang (College of Computer, National University of Defense Technology), Wei Xie (College of Computer, National University of Defense Technology), Xu Zhou (College of Computer,…

Read More