Results 31 to 40 of about 58,983 (255)
Privacy-Preserving Monotonicity of Differential Privacy Mechanisms
Applied Sciences, 2018 Differential privacy mechanisms can offer a trade-off between privacy and utility by using privacy metrics and utility metrics. The trade-off of differential privacy shows that one thing increases and another decreases in terms of privacy metrics and ...
Hai Liu +5 more
doaj +1 more source
Randomized Privacy Budget Differential Privacy
CoRR, 2022 arXiv admin note: text overlap with arXiv:2009 ...
openaire +2 more sources
Lemmas of Differential Privacy
CoRR, 2022 We aim to collect buried lemmas that are useful for proofs. In particular, we try to provide self-contained proofs for those lemmas and categorise them according to their usage.
Yiyang Huang, Clément L. Canonne
openaire +2 more sources
Combinational Randomized Response Mechanism for Unbalanced Multivariate Nominal Attributes
IEEE Access, 2020 At present, many enterprises provide users with better services by collecting their sensitive information. However, these enterprises will inevitably cause the leakage of users' information, thereby infringing on users' privacy.
Xuejie Feng +3 more
doaj +1 more source
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
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
Discrete Gaussian for Differential Privacy
Journal of Privacy and Confidentiality, 2022 A key tool for building differentially private systems is adding Gaussian noise to the output of a function evaluated on a sensitive dataset. Unfortunately, using a continuous distribution presents several practical challenges. First and foremost, finite computers cannot exactly represent samples from continuous distributions, and previous work has ...
Clément L. Canonne +2 more
openaire +5 more sources
Continual Learning with Differential Privacy [PDF]
, 2021 The paper will appear at ...
Pradnya Desai +3 more
openaire +2 more sources
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
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Medication nonadherence during the first 100 days after pediatric hematopoietic stem cell transplantation (HSCT) and during oncology treatment increases risk for complications. BMT4me is a caregiver‐facing mobile health (mHealth) application providing medication reminders, symptom tracking, and note‐taking features to support ...
Micah A. Skeens +4 more
wiley +1 more source