Dec 21, 2021 · Thus, in this work, we propose a stochastic perturbation method to sanitize the dataset, where the perturbation is obtained from the rest ...
Missing: (Extended | Show results with:(Extended
scholar.google.com › citations
Dec 31, 2023 · To preserve the privacy of IoT datasets, traditional methods usually calibrate random noises on the data values to achieve differential privacy ...
Data Level Privacy Preserving: A Stochastic Perturbation Approach Based on Differential Privacy (Extended abstract). 2024, pp. 5721-5722,. DOI Bookmark ...
To preserve the privacy of IoT datasets, traditional methods usually calibrate random noises on the data values to achieve differential privacy (DP) [1].
Apr 1, 2023 · Thus, in this work, we propose a stochastic perturbation method to sanitize the dataset, where the perturbation is obtained from the rest ...
Missing: (Extended | Show results with:(Extended
Jul 26, 2024 · Data Level Privacy Preserving: A Stochastic Perturbation Approach Based on Differential Privacy (Extended abstract) · No full-text available.
Apr 1, 2023 · Data Level Privacy Preserving: A Stochastic Perturbation Approach Based on Differential Privacy · Abstract · Full-Text PDF · Similar Papers ...
Missing: (Extended | Show results with:(Extended
To preserve the privacy of IoT datasets, traditional methods usually calibrate random noises on the data values to achieve differential privacy (DP). However, ...
Missing: (Extended | Show results with:(Extended
Article "Data Level Privacy Preserving: A Stochastic Perturbation Approach Based on Differential Privacy (Extended abstract)" Detailed information of the ...
Jul 30, 2024 · Data Level Privacy Preserving: A Stochastic Perturbation Approach Based on Differential Privacy (Extended abstract). ICDE 2024: 5721-5722.