重庆邮电大学学报（自然科学版）2023，Vol.35Issue(6)：1011-1019,9.DOI:10.3979/j.issn.1673-825X.202208200211
基于BIGRU的轨迹数据发布隐私保护方案
Privacy protection scheme for trajectory data publishing based on BIGRU
摘要
Abstract
While ensuring the privacy of trajectory data publication,it is necessary to improve the usability of the published data.Applying machine learning algorithms to trajectory data processing can improve the usability of trajectory data.A traj-ectory privacy protection scheme is proposed to solve the usability problem in trajectory data publishing,which combines bi-directional gated recurrent unit(BIGRU)and differential privacy(DP)for trajectory data publishing.Firstly,by applying BIGRU to preprocess trajectory data,the usability of trajectory data is improved.Then,the trajectory data is clustered and generalized,and a differential privacy index mechanism is used for partition selection to achieve privacy protection.Finally,the obtained generalized trajectory data set is subjected to exception handling and then gets published.Simulation results show that this scheme not only has good data usability,but also has certain efficiency advantages.关键词
差分隐私/轨迹数据发布/神经网络/轨迹预测/隐私保护Key words
differential privacy/trajectory data publishing/neural network/trajectory prediction/privacy protection分类
信息技术与安全科学引用本文复制引用
申艳梅,张玉阳,申自浩,王辉,刘沛骞..基于BIGRU的轨迹数据发布隐私保护方案[J].重庆邮电大学学报（自然科学版）,2023,35(6):1011-1019,9.基金项目
国家自然科学基金项目(61300216) （61300216）
河南省高等学校重点科研项目(23A520033) （23A520033）
河南理工大学博士基金项目(B2022-16)The National Natural Science Foundation of China(61300216) （B2022-16）
The Key Scientific Research Projects of Colleges and Universities in Henan Province(23A520033) （23A520033）
The PhD Foundation Project of Henan Polytechnic University(B2022-16) （B2022-16）
