Yue Qin (Indiana University Bloomington & Central University of Finance and Economics), Yue Xiao (Indiana University Bloomington & IBM Research), Xiaojing Liao (Indiana University Bloomington)

In privacy compliance research, a significant challenge lies in comparing specific data items in actual data usage practices with the privacy data defined in laws, regulations, or policies. This task is complex due to the diversity of data items used by various applications, as well as the different interpretations of privacy data across jurisdictions. To address this challenge, privacy data taxonomies have been constructed to capture relationships between privacy data types and granularity levels, facilitating privacy compliance analysis. However, existing taxonomy construction approaches are limited by manual efforts or heuristic rules, hindering their ability to incorporate new terms from diverse domains. In this paper, we present the design of GRASP, a scalable and efficient methodology for automatically constructing and expanding privacy data taxonomies. GRASP incorporates a novel hypernym prediction model based on granularity-aware semantic projection, which outperforms existing state-of-the-art hypernym prediction methods. Additionally, we design and implement Tracy, a privacy professional assistant to recognize and interpret private data in incident reports for GDPR-compliant data breach notification. We evaluate Tracy in a usability study with 15 privacy professionals, yielding high-level usability and satisfaction.

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Rethinking Trust in Forge-Based Git Security

Aditya Sirish A Yelgundhalli (New York University), Patrick Zielinski (New York University), Reza Curtmola (New Jersey Institute of Technology), Justin Cappos (New York University)

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WAVEN: WebAssembly Memory Virtualization for Enclaves

Weili Wang (Southern University of Science and Technology), Honghan Ji (ByteDance Inc.), Peixuan He (ByteDance Inc.), Yao Zhang (ByteDance Inc.), Ye Wu (ByteDance Inc.), Yinqian Zhang (Southern University of Science and Technology)

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Power-Related Side-Channel Attacks using the Android Sensor Framework

Mathias Oberhuber (Graz University of Technology), Martin Unterguggenberger (Graz University of Technology), Lukas Maar (Graz University of Technology), Andreas Kogler (Graz University of Technology), Stefan Mangard (Graz University of Technology)

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AI-Assisted RF Fingerprinting for Identification of User Devices in...

Aishwarya Jawne (Center for Connected Autonomy & AI, Florida Atlantic University), Georgios Sklivanitis (Center for Connected Autonomy & AI, Florida Atlantic University), Dimitris A. Pados (Center for Connected Autonomy & AI, Florida Atlantic University), Elizabeth Serena Bentley (Air Force Research Laboratory)

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