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.

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Fusion: Efficient and Secure Inference Resilient to Malicious Servers

Caiqin Dong (Jinan University), Jian Weng (Jinan University), Jia-Nan Liu (Jinan University), Yue Zhang (Jinan University), Yao Tong (Guangzhou Fongwell Data Limited Company), Anjia Yang (Jinan University), Yudan Cheng (Jinan University), Shun Hu (Jinan University)

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RR: A Fault Model for Efficient TEE Replication

Baltasar Dinis (Instituto Superior Técnico (IST-ULisboa) / INESC-ID / MPI-SWS), Peter Druschel (MPI-SWS), Rodrigo Rodrigues (Instituto Superior Técnico (IST-ULisboa) / INESC-ID)

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Work-in-Progress: Uncovering Dark Patterns: A Longitudinal Study of Cookie...

Zihan Qu (Johns Hopkins University), Xinyi Qu (University College London), Xin Shen, Zhen Liang, and Jianjia Yu (Johns Hopkins University)

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