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Randomized requantization with local differential privacy
2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2016In this paper we study how individual sensors can compress their observations in a privacy-preserving manner. We propose a randomized requantization scheme that guarantees local differential privacy, a strong model for privacy in which individual data holders must mask their information before sending it to an untrusted third party.
Sijie Xiong +2 more
openaire +1 more source
Towards Measuring Fairness for Local Differential Privacy
2023Local differential privacy (LDP) approaches provide data subjects with the strong privacy guarantees of Differential Privacy under the scenario of untrusted data curators. They are used by companies (e.g., Google’s RAPPOR) to collect potentially sensitive data from clients through randomized response.
Julián Salas +2 more
openaire +2 more sources
Local Differential Privacy for Data Streams
2020The dynamic change, huge data size, and complex structure of the data stream have made it very difficult to be analyzed and protected in real-time. Traditional privacy protection models such as differential privacy which need to rely on the trusted servers or companies, and this will increase the uncertainty of protecting streaming privacy.
Xianjin Fang, Qingkui Zeng, Gaoming Yang
openaire +1 more source
Multiple Privacy Regimes Mechanism for Local Differential Privacy
2019Local differential privacy (LDP), as a state-of-the-art privacy notion, enables users to share protected data safely while the private real data never leaves user’s device. The privacy regime is one of the critical parameters balancing between the correctness of the statistical result and the level of user’s privacy.
Yutong Ye 0002 +4 more
openaire +1 more source
A novel local differential privacy federated learning under multi-privacy regimes
Expert Systems With Applications, 2023Jinchuan Tang, Shuping Dang
exaly
PPeFL: Privacy-Preserving Edge Federated Learning With Local Differential Privacy
IEEE Internet of Things Journal, 2023Baocang Wang, Yange Chen, Zhen Zhao
exaly
Local Differential Privacy for data collection and analysis
Neurocomputing, 2021Teng Wang, Zhi Hu, Xinyu Yang
exaly
Key-value data collection and statistical analysis with local differential privacy
Information Sciences, 2023Laurence T Yang
exaly
Local differential privacy for social network publishing
Neurocomputing, 2020Yuanxin Xu, Li-E Wang, Xianxian Li
exaly
Community-based social recommendation under local differential privacy protection
Information Sciences, 2023Taolin Guo, Yong Li, Mingliang Zhou
exaly