Shuwen Liu (School of Data Science, The Chinese University of Hong Kong, Shenzhen, China), George C. Polyzos (School of Data Science, The Chinese University of Hong Kong, Shenzhen, China and ExcID P.C., Athens, Greece)

We design a privacy-preserving data proxy mechanism within the FIWARE Data Space framework, utilizing searchable encryption to ensure metadata confidentiality. The system is engineered to enable secure and efficient data querying, hiding the queries from the proxy and other data in the proxy from the querying agent. Recognizing the necessity of regulatory compliance, this paper integrates GDPR compliance modules into the FIWARE Data Space architecture, addressing data collection, storage, sharing, and erasure processes to enhance global applicability and regulatory adherence. In essence, we preserve metadata privacy. Experimental evaluations demonstrate the feasibility of the proposed query privacy mechanisms, focusing on metadata confidentiality and system scalability in data-intensive environments.

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ICSQuartz: Scan Cycle-Aware and Vendor-Agnostic Fuzzing for Industrial Control...

Corban Villa (New York University Abu Dhabi), Constantine Doumanidis (New York University Abu Dhabi), Hithem Lamri (New York University Abu Dhabi), Prashant Hari Narayan Rajput (InterSystems), Michail Maniatakos (New York University Abu Dhabi)

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Diffence: Fencing Membership Privacy With Diffusion Models

Yuefeng Peng (University of Massachusetts Amherst), Ali Naseh (University of Massachusetts Amherst), Amir Houmansadr (University of Massachusetts Amherst)

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Provably Unlearnable Data Examples

Derui Wang (CSIRO's Data61), Minhui Xue (CSIRO's Data61), Bo Li (The University of Chicago), Seyit Camtepe (CSIRO's Data61), Liming Zhu (CSIRO's Data61)

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