Titlebook: Data and Applications Security and Privacy XXXVII; 37th Annual IFIP WG Vijayalakshmi Atluri,Anna Lisa Ferrara Conference proceedings 2023

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Left-Atrium

https://doi.org/10.1007/978-3-540-47590-3ightly improved fairness in learning problems without significantly affecting the performance of the models. We conduct extensive experiments evaluating three benchmark datasets using several group fairness metrics and seven state-of-the-art LDP protocols. Overall, this study challenges the common b

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PASTA and NAPLES: Rheology Simulatorch can be used to share independent secrets having different sizes. The protocol can manage any kind of graph and generalizes previous protocols for secrets having the same sizes, while maintaining optimal storage requirements.

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S. Fraga,J. M. R. Parker,J. M. Pocockngerprinting codes as a part of the proposed scheme. We implement and evaluate the performance of the proposed scheme on real genomic data. Our experimental results show the efficiency and robustness of the proposed scheme.

FELON

S. Fraga,J. M. R. Parker,J. M. Pocockonal bootstrapping for implementing Grain128-AEAD in a more efficient base (.) representation, rather than a binary one. This significantly reduces the overall number of necessary bootstrappings in a homomorphic run of the stream-cipher, for example reducing the number of bootstrappings required in

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S. Fraga,J. M. R. Parker,J. M. Pocockor worse than others; also, the temporal dimension was particularly sensitive, with scores decreasing up to . between the original and the transformed data. This shows the effect of different levels of data privacy on the data utility of IoT applications, and can also help to identify which paramete

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