RNN-DP: A new differential privacy scheme base on Recurrent Neural Network for Dynamic trajectory privacy protection-Reference-Cited by-同舟云学术

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RNN-DP: A new differential privacy scheme base on Recurrent Neural Network for Dynamic trajectory privacy protection

Published:2020-10 Issue: Volume:168 Page:102736
ISSN:1084-8045
Container-title:Journal of Network and Computer Applications
language:en
Short-container-title:Journal of Network and Computer Applications

Author:

Chen Si,Fu Anmin,Shen Jian,Yu Shui,Wang Huaqun,Sun Huaijiang

Funder

National Natural Science Foundation of China

Central

Jiangsu Key Laboratory of Big Data Security & Intelligent Processing

Publisher

Elsevier BV

Subject

Computer Networks and Communications,Computer Science Applications,Hardware and Architecture

Reference41 articles.

1. Synthesizing plausible privacy-preserving location traces;Bindschaedler,2016

2. Differentially private sequential data publication via variable-length n-grams;Chen,2012

3. Privacy-preserving trajectory data publishing by local suppression;Chen;Inf. Sci.,2013

4. Differential privacy;Dwork;Lect. Notes Comput. Sci.,2006

5. Differential privacy and robust statistics;Dwork,2009

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4. VLIA: Navigating Shadows with Proximity for Highly Accurate Visited Location Inference Attack against Federated Recommendation Models;Proceedings of the 19th ACM Asia Conference on Computer and Communications Security;2024-07

5. Federated TimeGAN for Privacy Preserving Synthetic Trajectory Generation;2024 25th IEEE International Conference on Mobile Data Management (MDM);2024-06-24

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