Results 31 to 40 of about 166,775,831 (215)
On the Risk of Opening Distributed Keys [PDF]
, 2007 We describe an insider known-key attack on key distribution systems which are based on public keys. This is of a general type and applies to the key distribution system presented by Yacobi at Crypto '90, the Goss system, the Gunther system presented at Eurocrypt '89 and the key exchange version of COMSET, based on a system presented by Brandt et al. at
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Formalizing and Estimating Distribution Inference Risks
Proceedings on Privacy Enhancing Technologies, 2022 Distribution inference, sometimes called property inference, infers statistical properties about a training set from access to a model trained on that data. Distribution inference attacks can pose serious risks when models are trained on private data, but are difficult to distinguish from the intrinsic purpose of statistical machine learning—namely, to
Anshuman Suri, David Evans 0001
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Pseudonymization risk analysis in distributed systems [PDF]
Journal of Internet Services and Applications, 2019 In an era of big data, online services are becoming increasingly data-centric; they collect, process, analyze and anonymously disclose growing amounts of personal data in the form of pseudonymized data sets. It is crucial that such systems are engineered to both protect individual user (data subject) privacy and give back control of personal data to ...
Geoffrey Neumann +3 more
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MoleculesMicroplastic (MP) pollution in bottled and tap water poses escalating environmental and public health challenges due to MPs’ capacity to act as vectors for toxicants and pathogens.
Mariana Silva +5 more
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Analysis of Type-II Censored Competing Risks’ Data under Reduced New Modified Weibull Distribution
Complexity, 2021 Models with the bathtub-shaped hazard rate function are widely used in lifetime analysis and reliability engineering. In this paper, we adopted the reduced new modified Weibull (RNMW) distribution with a bathtub-shaped hazard rate function.
Saad J. Almalki +3 more
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Spatio-temporal Distribution and Ecological Risks of Persistent Organic Pollutants in Artificial Canal [PDF]
长江科学院院报[Objective] This study aims to systematically characterize the spatiotemporal distribution patterns and ecological risk levels of persistent organic pollutants (POPs)—including polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs ...
SUN Jing-jie, WANG Zhi-yuan, WANG Yi-hong, ZHU Qiu-heng, LIU Dong-sheng, SHI Yi-fan, HUANG Yu, XU Jia-xin
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Identification and ranking of technology risks in the field of natural gas energy distribution by the integrative approach of FMEA and TOPSIS The Case of Chaharmahal and Bakhtiari Province Gas Company [PDF]
مدیریت تولید و عملیات, 2019 Purpose: One of the most important risks of organizations is technology risk. In gas companies, due to the expansion of activities, increase in the number of subscribers, and increase share of gas in energy basket, technology has a very important role in
Mahdi Nakhaeinejad, Maesoomeh Safari
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Distributed Inference for Tail Risks
Statistica SinicaFor measuring tail risk with scarce extreme events, extreme value analysis is often invoked as the statistical tool to extrapolate to the tail of a distribution. The presence of large datasets benefits tail risk analysis by providing more observations for conducting extreme value analysis.
Chen, Liujun, Li, D (Deyuan), Zhou, Chen
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Distribution of major health risks: findings from the Global Burden of Disease study.
PLoS Medicine, 2004 BackgroundMost analyses of risks to health focus on the total burden of their aggregate effects. The distribution of risk-factor-attributable disease burden, for example by age or exposure level, can inform the selection and targeting of specific ...
Anthony Rodgers +6 more
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Risk Bounds For Distributional Regression
CoRRThis work examines risk bounds for nonparametric distributional regression estimators. For convex-constrained distributional regression, general upper bounds are established for the continuous ranked probability score (CRPS) and the worst-case mean squared error (MSE) across the domain.
Carlos Misael Madrid Padilla +2 more
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