Carlotta Tagliaro (TU Wien), Florian Hahn (University of Twente), Riccardo Sepe (Guess Europe Sagl), Alessio Aceti (Sababa Security SpA), Martina Lindorfer (TU Wien)

The ever-increasing popularity of Smart TVs and support for the Hybrid Broadcast Broadband TV (HbbTV) standard allow broadcasters to enrich content offered to users via the standard broadcast signal with Internet-delivered apps, e.g., ranging from quizzes during a TV show to targeted advertisement. HbbTV works using standard web technologies as transparent overlays over a TV channel. Despite the number of HbbTV-enabled devices rapidly growing, studies on the protocol's security and privacy aspects are scarce, and no standard protective measure is in place.

We fill this gap by investigating the current state of HbbTV in the European landscape and assessing its implications for users' privacy. We shift the focus from the Smart TV's firmware and app security, already studied in-depth in related work, to the content transmission protocol itself. Contrary to traditional ``linear TV'' signals, HbbTV allows for bi-directional communication: in addition to receiving TV content, it also allows for transmitting data back to the broadcaster. We describe techniques broadcasters use to measure users' (viewing) preferences and show how the protocol's implementation can cause severe privacy risks by studying its deployment by 36 TV channels in five European countries (Italy, Germany, France, Austria, and Finland). We also survey users' awareness of Smart TV and HbbTV-related risks. Our results show little understanding of the possible threats users are exposed to. Finally, we present a denylist-based mechanism to ensure a safe experience for users when watching TV and to reduce the privacy issues that HbbTV may pose.

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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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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…

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Kaustav Bhattacharjee, Aritra Dasgupta (New Jersey Institute of Technology)

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CHKPLUG: Checking GDPR Compliance of WordPress Plugins via Cross-language...

Faysal Hossain Shezan (University of Virginia), Zihao Su (University of Virginia), Mingqing Kang (Johns Hopkins University), Nicholas Phair (University of Virginia), Patrick William Thomas (University of Virginia), Michelangelo van Dam (in2it), Yinzhi Cao (Johns Hopkins University), Yuan Tian (UCLA)

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