Results 81 to 90 of about 212,227 (315)
Actual Knowledge Gain as Privacy Loss in Local Privacy Accounting [PDF]
arXiv, 2023 This paper establishes the equivalence between Local Differential Privacy (LDP) and a global limit on learning any knowledge specific to a queried object. However, an output from an LDP query is not necessarily required to provide exact amount of knowledge equal to the upper bound of the learning limit.
arxiv
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
doaj +1 more source
Concentrated Differential Privacy [PDF]
arXiv, 2016 We introduce Concentrated Differential Privacy, a relaxation of Differential Privacy enjoying better accuracy than both pure differential privacy and its popular "(epsilon,delta)" relaxation without compromising on cumulative privacy loss over multiple computations.
arxiv
Algorithms with More Granular Differential Privacy Guarantees [PDF]
arXiv, 2022 Differential privacy is often applied with a privacy parameter that is larger than the theory suggests is ideal; various informal justifications for tolerating large privacy parameters have been proposed. In this work, we consider partial differential privacy (DP), which allows quantifying the privacy guarantee on a per-attribute basis.
arxiv
Asymmetric Differential Privacy
, 2021 Differential privacy (DP) is getting attention as a privacy definition when publishing statistics of a dataset. This paper focuses on the limitation that DP inevitably causes two-sided error, which is not desirable for epidemic analysis such as how many COVID-19 infected individuals visited location A.
Takagi, Shun +2 more
openaire +2 more sources
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
doaj +2 more sources
Reconstruction Attacks on Aggressive Relaxations of Differential Privacy
The Journal of Privacy and ConfidentialityDifferential privacy is a widely accepted formal privacy definition that allows aggregate information about a dataset to be released while controlling privacy leakage for individuals whose records appear in the data.
Prottay Protivash +4 more
doaj +1 more source
Position Paper on Simulating Privacy Dynamics in Recommender Systems [PDF]
arXiv, 2021 In this position paper, we discuss the merits of simulating privacy dynamics in recommender systems. We study this issue at hand from two perspectives: Firstly, we present a conceptual approach to integrate privacy into recommender system simulations, whose key elements are privacy agents. These agents can enhance users' profiles with different privacy
arxiv
Journal of Applied Clinical Medical Physics, EarlyView.Abstract Background This study aims to develop a novel predictive model for determining human papillomavirus (HPV) presence in oropharyngeal cancer using computed tomography (CT). Current image‐based HPV prediction methods are hindered by high computational demands or suboptimal performance.
Junhua Chen +3 more
wiley +1 more source
Journal of Applied Clinical Medical Physics, EarlyView.Abstract Current radiotherapy practices rely on manual contouring of CT scans, which is time‐consuming, prone to variability, and requires highly trained experts. There is a need for more efficient and consistent contouring methods. This study evaluated the performance of the Varian Ethos AI auto‐contouring tool to assess its potential integration into
Robert N. Finnegan +6 more
wiley +1 more source