Results 61 to 70 of about 56,445 (299)
On the 'Semantics' of Differential Privacy: A Bayesian Formulation
The Journal of Privacy and Confidentiality, 2014 Differential privacy is a definition of privacy for algorithms that analyze and publish information about statistical databases. It is often claimed that differential privacy provides guarantees against adversaries with arbitrary side information.
Shiva P. Kasiviswanathan, Adam Smith
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Journal of Machine LearningDifferential privacy is a framework for protecting the identity of individual data points in the decision-making process. In this note, we propose a new form of differential privacy called tangent differential privacy. Compared with the usual differential privacy that is defined uniformly across data distributions, tangent differential privacy is ...
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Molecular Oncology, EarlyView.The cancer problem is increasing globally with projections up to the year 2050 showing unfavourable outcomes in terms of incidence and cancer‐related deaths. The main challenges are prevention, improved therapeutics resulting in increased cure rates and enhanced health‐related quality of life.
Ulrik Ringborg +43 more
wiley +1 more source
Have the cake and eat it too: Differential Privacy enables privacy and precise analytics
Journal of Big Data, 2023 Existing research in differential privacy, whose applications have exploded across functional areas in the last few years, describes an intrinsic trade-off between the privacy of a dataset and its utility for analytics.
Rishabh Subramanian
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Liftings for Differential Privacy
, 2017 Recent developments in formal verification have identified approximate liftings (also known as approximate couplings) as a clean, compositional abstraction for proving differential privacy. There are two styles of definitions for this construction. Earlier definitions require the existence of one or more witness distributions, while a recent definition
Barthe, Gilles +4 more
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Molecular Oncology, EarlyView.This study shows that copy number variations (CNVs) can be reliably detected in formalin‐fixed paraffin‐embedded (FFPE) solid cancer samples using ultra‐low‐pass whole‐genome sequencing, provided that key (pre)‐analytical parameters are optimized.
Hanne Goris +10 more
wiley +1 more source
Trajectory differential privacy protection mechanism based on prediction and sliding window
Tongxin xuebao, 2020 To address the issues of privacy budget and quality of service in trajectory differential privacy protection,a trajectory differential privacy mechanism integrating prediction disturbance was proposed.Firstly,Markov chain and exponential perturbation ...
Ayong YE +4 more
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Privacy Protection from Sampling and Perturbation in Survey Microdata
The Journal of Privacy and Confidentiality, 2012 Statistical agencies release microdata from social surveys as public-use files after applying statistical disclosure limitation (SDL) techniques. Disclosure risk is typically assessed in terms of identification risk, where it is supposed that small ...
Natalie Shlomo, Chris J. Skinner
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FEBS Open Bio, EarlyView.Comparative analysis of chloroplast genomes from 14 genera of Thymelaeaceae revealed variation in gene content, ranging from 128 to 142 genes, primarily influenced by IR expansion/contraction events and pseudogenization of ndhF, ndhI, and ndhG. Two large inversions were detected within the large single‐copy region, including a synapomorphic inversion ...
Abdullah +8 more
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