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Titlebook: Data Privacy Management and Security Assurance; 11th International W Giovanni Livraga,Vicen? Torra,Neeraj Suri Conference proceedings 2016

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樓主: JAR
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發(fā)表于 2025-3-30 11:47:12 | 只看該作者
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發(fā)表于 2025-3-30 16:08:32 | 只看該作者
Metrics for Transparency to information concerning the system’s processes, clarifying who is responsible if something goes wrong. Thus, it is believed to support people’s right to a secure and private processing of their personal data. We define eight quality metrics for transparency and we demonstrate the usage and the ef
53#
發(fā)表于 2025-3-30 20:34:38 | 只看該作者
Understanding Bifurcation of Slow Versus Fast Cyber-Attackersr hand is well known. In this article, we provide an explanation for this phenomenon as the outcome of an optimization from the perspective of the attacker. To this end, we model attacks as an interaction between an attacker and a defender and infer the two types of behavior observed based on justif
54#
發(fā)表于 2025-3-30 22:26:27 | 只看該作者
Decomposing Global Quantitative Properties into Local Onesrity) property on the behaviour of the whole system. We associate each action with a value. Hence, we end up with quantitative properties on them, which are specified through a modal logic equipped with a parametric algebraic structure (i.e., a c-semiring). The aim is to have a value related to the
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發(fā)表于 2025-3-31 03:49:47 | 只看該作者
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發(fā)表于 2025-3-31 06:00:30 | 只看該作者
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發(fā)表于 2025-3-31 11:21:43 | 只看該作者
Privacy-Preserving Abuse Detection in Future Decentralised Online Social Networkss participants in the network. We investigate the use of supervised learning techniques to detect abusive behavior and describe privacy-preserving protocols to compute the feature set required by abuse classification algorithms in a secure and privacy-preserving way. While our method is not yet full
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發(fā)表于 2025-3-31 16:25:32 | 只看該作者
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發(fā)表于 2025-3-31 20:16:45 | 只看該作者
Searchable Encryption for Biometric Identification Revisitedation of symmetric searchable encryption (SSE) to biometric identification. Our main contribution is two SSE schemes well-suited to be applied to biometric identification over encrypted data. While existing solution uses SSE with single-keyword search and highly sequential design, we use threshold c
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