Tianhang Zheng (University of Missouri-Kansas City), Baochun Li (University of Toronto)

Recent work in ICML’22 established a connection between dataset condensation (DC) and differential privacy (DP), which is unfortunately problematic. To correctly connect DC and DP, we propose two differentially private dataset condensation (DPDC) algorithms—LDPDC and NDPDC. LDPDC is a linear DC algorithm that can be executed on a low-end Central Processing Unit (CPU), while NDPDC is a nonlinear DC algorithm that leverages neural networks to extract and match the latent representations between real and synthetic data. Through extensive evaluations, we demonstrate that LDPDC has comparable performance to recent DP generative methods despite its simplicity. NDPDC provides acceptable DP guarantees with a mild utility loss, compared to distribution matching (DM). Additionally, NDPDC allows a flexible trade-off between the synthetic data utility and DP budget.

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The CURE to Vulnerabilities in RPKI Validation

Donika Mirdita (Technische Universität Darmstadt), Haya Schulmann (Goethe-Universität Frankfurt), Niklas Vogel (Goethe-Universität Frankfurt), Michael Waidner (Technische Universität Darmstadt, Fraunhofer SIT)

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Space-Domain AI Applications need Rigorous Security Risk Analysis

Alexandra Weber (Telespazio Germany GmbH), Peter Franke (Telespazio Germany GmbH)

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Flow Correlation Attacks on Tor Onion Service Sessions with...

Daniela Lopes (INESC-ID / IST, Universidade de Lisboa), Jin-Dong Dong (Carnegie Mellon University), Pedro Medeiros (INESC-ID / IST, Universidade de Lisboa), Daniel Castro (INESC-ID / IST, Universidade de Lisboa), Diogo Barradas (University of Waterloo), Bernardo Portela (INESC TEC / Universidade do Porto), João Vinagre (INESC TEC / Universidade do Porto), Bernardo Ferreira (LASIGE, Faculdade de…

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WIP: A Trust Assessment Method for In-Vehicular Networks using...

Artur Hermann, Natasa Trkulja (Ulm University - Institute of Distributed Systems), Anderson Ramon Ferraz de Lucena, Alexander Kiening (DENSO AUTOMOTIVE Deutschland GmbH), Ana Petrovska (Huawei Technologies), Frank Kargl (Ulm University - Institute of Distributed Systems)

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