Results 51 to 60 of about 212,227 (315)
Age-Dependent Differential Privacy
IEEE Transactions on Information Theory, 2022 The proliferation of real-time applications has motivated extensive research on analyzing and optimizing data freshness in the context of age of information. However, classical frameworks of privacy (e.g., differential privacy (DP)) have overlooked the impact of data freshness on privacy guarantees, and hence may lead to unnecessary accuracy loss when ...
Meng Zhang +3 more
openaire +2 more sources
Differential Privacy in Practice: Expose your Epsilons!
The Journal of Privacy and Confidentiality, 2019 Differential privacy is at a turning point. Implementations have been successfully leveraged in private industry, the public sector, and academia in a wide variety of applications, allowing scientists, engineers, and researchers the ability to learn ...
Cynthia Dwork +2 more
doaj +1 more source
The Protection of Data Sharing for Privacy in Financial Vision
Applied Sciences, 2022 The primary motivation is to address difficulties in data interpretation or a reduction in model accuracy. Although differential privacy can provide data privacy guarantees, it also creates problems.
Yi-Ren Wang, Yun-Cheng Tsai
doaj +1 more source
FL-ODP: An Optimized Differential Privacy Enabled Privacy Preserving Federated Learning
IEEE Access, 2023 Privacy-preserving methods and techniques aim to safeguard the privacy of individuals and groups while facilitating data sharing for specific purposes.
Maria Iqbal +4 more
doaj +1 more source
Reconstruction Attacks on Aggressive Relaxations of Differential Privacy [PDF]
arXiv, 2022 Differential 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. Due to the unavoidable tension between privacy and utility, there have been many works trying to relax the requirements of differential ...
arxiv
Randori: Local Differential Privacy for All [PDF]
arXiv, 2021 Polls are a common way of collecting data, including product reviews and feedback forms. However, few data collectors give upfront privacy guarantees. Additionally, when privacy guarantees are given upfront, they are often vague claims about 'anonymity'.
arxiv
Privacy-Preserving Bin-Packing With Differential Privacy
IEEE Open Journal of Signal Processing, 2022 With the emerging of e-commerce, package theft is at a high level: It is reported that 1.7 million packages are stolen or lost every day in the U.S. in 2020, which costs $25 million every day for the lost packages and the service.
Tianyu Li +2 more
doaj +1 more source
Differential Privacy as a Mutual Information Constraint [PDF]
, 2016 Differential privacy is a precise mathematical constraint meant to ensure privacy of individual pieces of information in a database even while queries are being answered about the aggregate. Intuitively, one must come to terms with what differential privacy does and does not guarantee.
arxiv +1 more source
Survey on differential privacy and its progress
Tongxin xuebao, 2017 With the arrival of the era of big data sharing,data privacy protection issues will be highlighted.Since its introduction in 2006,differential privacy technology has been widely researched in data mining and data publishing.In recent years,Google,Apple ...
Zhi-qiang GAO, Yu-tao WANG
doaj +2 more sources
Differentially Private Mixed Data Release Algorithm Based on k-prototype Clustering
Jisuanji kexue yu tansuo, 2021 Differential privacy is a model that provides strong privacy protection. Under the non-interactive frame-work, data managers can publish data sets processed by differential privacy protection technology for researchers to conduct mining and analysis ...
QU Jingjing, CAI Ying, FAN Yanfang, XIA Hongke
doaj +1 more source