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Relations Between Several Classical Privacy Notions
- ACTA ELECTRONICA SINICA Vol. 53, Issue 10, Pages: 3781-3793(2025)
- 作者机构：
1.亚洲大学人工智能系，韩国水原 16499
2.复旦大学计算机科学技术学院，上海 200433
3.兰州理工大学计算机与人工智能学院， 甘肃兰州 730050
4.湘潭大学数学与计算科学学院，湖南湘潭 411105
5.暨南大学信息科学技术学院，广东广州 510632
- 作者简介：
- 基金信息：National Natural Science Foundation of China(W2411053)
DOI：10.12263/DZXB.20250078
CLC： TP3-05;O211.1Received：22 January 2025，
Accepted：25 September 2025，
Published：25 October 2025
- 稿件说明：
移动端阅览
郑智润, 黄橙, 王萍, 等. 几类经典隐私定义间的关系[J]. 电子学报, 2025, 53(10): 3781-3793.
ZHENG Zhi-run, HUANG Cheng, WANG Ping, et al. Relations Between Several Classical Privacy Notions[J]. Acta Electronica Sinica, 2025, 53(10): 3781-3793.
郑智润, 黄橙, 王萍, 等. 几类经典隐私定义间的关系[J]. 电子学报, 2025, 53(10): 3781-3793. DOI：10.12263/DZXB.20250078
ZHENG Zhi-run, HUANG Cheng, WANG Ping, et al. Relations Between Several Classical Privacy Notions[J]. Acta Electronica Sinica, 2025, 53(10): 3781-3793. DOI：10.12263/DZXB.20250078
摘要
针对现有基于不同隐私定义设计的扰动机制在理论上难以比较优劣的问题，本文从理论层面深入分析了中心化场景和本地化场景下可辨识性、差分隐私和互信息隐私这三类经典隐私定义之间的关系，构建了一个完备的隐私定义框架.具体而言，给定由真实数据先验概率分布决定的常数（当先验概率分布为均匀分布时，常数
<math id="M1"><msub><mrow><mi>σ</mi></mrow><mrow><mi mathvariant="normal">m</mi><mi mathvariant="normal">i</mi><mi mathvariant="normal">n</mi></mrow></msub><mo>=</mo><mn mathvariant="normal">0</mn></math>
https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=99951070&type=
https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=99951080&type=
8.89000034
3.21733332
），可得以下结论：满足
<math id="M2"><msub><mrow><mi>ε</mi></mrow><mrow><mi>i</mi></mrow></msub></math>
https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=99951097&type=
https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=99951071&type=
1.94733346
3.21733332
-可辨识性的隐私保护机制必然也同时满足
<math id="M3"><mfenced separators="|"><mrow><msub><mrow><mi>ε</mi></mrow><mrow><mi>i</mi></mrow></msub><mo>-</mo><msub><mrow><mi>σ</mi></mrow><mrow><mi mathvariant="normal">m</mi><mi mathvariant="normal">i</mi><mi mathvariant="normal">n</mi></mrow></msub></mrow></mfenced></math>
https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=99951110&type=
https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=99951098&type=
11.68400002
3.80999994
-差分隐私和
<math id="M4"><mn mathvariant="normal">2</mn><mfenced separators="|"><mrow><msub><mrow><mi>ε</mi></mrow><mrow><mi>i</mi></mrow></msub><mo>-</mo><msub><mrow><mi>σ</mi></mrow><mrow><mi mathvariant="normal">m</mi><mi mathvariant="normal">i</mi><mi mathvariant="normal">n</mi></mrow></msub></mrow></mfenced></math>
https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=99951087&type=
https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=99951121&type=
13.80066681
3.80999994
-互信息隐私；满足
<math id="M5"><msub><mrow><mi>ε</mi></mrow><mrow><mi>d</mi></mrow></msub></math>
https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=99951113&type=
https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=99951112&type=
2.28600001
3.21733332
-差分隐私的隐私保护机制必然也同时满足
<math id="M6"><mfenced separators="|"><mrow><msub><mrow><mi>ε</mi></mrow><mrow><mi>d</mi></mrow></msub><mo>+</mo><msub><mrow><mi>σ</mi></mrow><mrow><mi mathvariant="normal">m</mi><mi mathvariant="normal">i</mi><mi mathvariant="normal">n</mi></mrow></msub></mrow></mfenced></math>
https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=99951115&type=
https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=99951125&type=
12.10733318
3.89466691
-可辨识性和
<math id="M7"><mn mathvariant="normal">2</mn><msub><mrow><mi>ε</mi></mrow><mrow><mi>d</mi></mrow></msub></math>
https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=99951151&type=
https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=99951150&type=
3.89466691
3.21733332
-互信息隐私；但是，满足
<math id="M8"><msub><mrow><mi>ε</mi></mrow><mrow><mi>m</mi></mrow></msub></math>
https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=99951153&type=
https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=99951140&type=
2.70933342
3.21733332
-互信息隐私的隐私保护机制却不一定满足
<math id="M9"><msub><mrow><mi>ε</mi></mrow><mrow><mi>i</mi></mrow></msub></math>
https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=99951166&type=
https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=99951142&type=
1.94733346
3.21733332
-可辨识性和
<math id="M10"><msub><mrow><mi>ε</mi></mrow><mrow><mi>d</mi></mrow></msub></math>
https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=99951168&type=
https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=99951156&type=
2.28600001
3.21733332
-差分隐私（在
<math id="M11"><msub><mrow><mi>ε</mi></mrow><mrow><mi>m</mi></mrow></msub></math>
https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=99951180&type=
https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=99951169&type=
2.70933342
3.21733332
有限的情况下，
<math id="M12"><msub><mrow><mi>ε</mi></mrow><mrow><mi>i</mi></mrow></msub></math>
https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=99951172&type=
https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=99951181&type=
1.94733346
3.21733332
和
<math id="M13"><msub><mrow><mi>ε</mi></mrow><mrow><mi>d</mi></mrow></msub></math>
https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=99951168&type=
https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=99951156&type=
2.28600001
3.21733332
可能会趋于无穷大）.此外，所提隐私定义框架能一致地推导出隐私定义间的关系，使得对隐私预算上界的估计更加准确.
Abstract
We address the challenge of theoretically evaluating various perturbation-based privacy-preserving mechanisms designed under different privacy notions. By analyzing the relationships among three classical privacy notions
namely identifiability
differential privacy
and mutual-information privacy
in both centralized and local settings
we propose a complete privacy notion framework that establishes theoretical relations among them. Specifically
given a constant
<math id="M14"><msub><mrow><mi>σ</mi></mrow><mrow><mi mathvariant="normal">m</mi><mi mathvariant="normal">i</mi><mi mathvariant="normal">n</mi></mrow></msub></math>
https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=99951196&type=
https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=99951173&type=
4.48733330
3.21733332
determined by the prior probability distribution of the real data (the constant
<math id="M15"><msub><mrow><mi>σ</mi></mrow><mrow><mi mathvariant="normal">m</mi><mi mathvariant="normal">i</mi><mi mathvariant="normal">n</mi></mrow></msub><mo>=</mo><mn mathvariant="normal">0</mn></math>
https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=99951186&type=
https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=99951176&type=
8.89000034
3.21733332
when the prior distribution is uniform)
the following theorems are formally proved in both central and local settings. First
the mechanism satisfying
<math id="M16"><msub><mrow><mi>ε</mi></mrow><mrow><mi>i</mi></mrow></msub></math>
https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=99951202&type=
https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=99951213&type=
1.94733346
3.21733332
-identifiability must also satisfy
<math id="M17"><msub><mrow><mi>ε</mi></mrow><mrow><mi>d</mi></mrow></msub></math>
https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=99951204&type=
https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=99951203&type=
2.28600001
3.21733332
-differential privacy with
<math id="M18"><msub><mrow><mi>ε</mi></mrow><mrow><mi>d</mi></mrow></msub><mo>=</mo><msub><mrow><mi>ε</mi></mrow><mrow><mi>i</mi></mrow></msub><mo>-</mo><msub><mrow><mi>σ</mi></mrow><mrow><mi mathvariant="normal">m</mi><mi mathvariant="normal">i</mi><mi mathvariant="normal">n</mi></mrow></msub></math>
https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=99951218&type=
https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=99951205&type=
14.22399998
3.21733332
. Second
the mechanism satisfying
<math id="M19"><msub><mrow><mi>ε</mi></mrow><mrow><mi>d</mi></mrow></msub></math>
https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=99951241&type=
https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=99951240&type=
2.28600001
3.21733332
-differential privacy must also satisfy
<math id="M20"><msub><mrow><mi>ε</mi></mrow><mrow><mi>i</mi></mrow></msub></math>
https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=99951202&type=
https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=99951213&type=
1.94733346
3.21733332
-identifiability with
<math id="M21"><msub><mrow><mi>ε</mi></mrow><mrow><mi>i</mi></mrow></msub><mo>=</mo><msub><mrow><mi>ε</mi></mrow><mrow><mi>d</mi></mrow></msub><mo>+</mo><msub><mrow><mi>σ</mi></mrow><mrow><mi mathvariant="normal">m</mi><mi mathvariant="normal">i</mi><mi mathvariant="normal">n</mi></mrow></msub></math>
https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=99951255&type=
https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=99951254&type=
14.22399998
3.21733332
. Third
the mechanism satisfying
<math id="M22"><msub><mrow><mi>ε</mi></mrow><mrow><mi>i</mi></mrow></msub></math>
https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=99951245&type=
https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=99951233&type=
1.94733346
3.21733332
-identifiability must also satisfy
<math id="M23"><msub><mrow><mi>ε</mi></mrow><mrow><mi>m</mi></mrow></msub></math>
https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=99951247&type=
https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=99951235&type=
2.70933342
3.21733332
-mutual-information privacy with
<math id="M24"><msub><mrow><mi>ε</mi></mrow><mrow><mi>m</mi></mrow></msub><mo>=</mo><mn mathvariant="normal">2</mn><mo stretchy="false">(</mo><msub><mrow><mi>ε</mi></mrow><mrow><mi>i</mi></mrow></msub><mo>-</mo><msub><mrow><mi>σ</mi></mrow><mrow><mi mathvariant="normal">m</mi><mi mathvariant="normal">i</mi><mi mathvariant="normal">n</mi></mrow></msub><mo stretchy="false">)</mo></math>
https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=99951261&type=
https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=99951260&type=
18.54199982
3.89466691
. Fourth
the mechanism satisfying
<math id="M25"><msub><mrow><mi>ε</mi></mrow><mrow><mi>m</mi></mrow></msub></math>
https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=99951263&type=
https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=99951262&type=
2.70933342
3.21733332
-mutual-information privacy does not guarantee
<math id="M26"><msub><mrow><mi>ε</mi></mrow><mrow><mi>d</mi></mrow></msub></math>
https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=99951265&type=
https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=99951276&type=
2.28600001
3.21733332
-differential privacy. Fifth
the mechanism satisfying
<math id="M27"><msub><mrow><mi>ε</mi></mrow><mrow><mi>d</mi></mrow></msub></math>
https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=99951298&type=
https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=99951286&type=
2.28600001
3.21733332
-differential privacy must also satisfy
<math id="M28"><msub><mrow><mi>ε</mi></mrow><mrow><mi>m</mi></mrow></msub></math>
https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=99951288&type=
https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=99951279&type=
2.70933342
3.21733332
-mutual-information privacy with
<math id="M29"><msub><mrow><mi>ε</mi></mrow><mrow><mi>m</mi></mrow></msub><mo>=</mo><mn mathvariant="normal">2</mn><msub><mrow><mi>ε</mi></mrow><mrow><mi>d</mi></mrow></msub></math>
https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=99951301&type=
https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=99951289&type=
9.39799976
3.21733332
. Sixth
the mechanism satisfying
<math id="M30"><msub><mrow><mi>ε</mi></mrow><mrow><mi>m</mi></mrow></msub></math>
https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=99951291&type=
https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=99951314&type=
2.70933342
3.21733332
-mutual-information privacy does not guarantee
<math id="M31"><msub><mrow><mi>ε</mi></mrow><mrow><mi>d</mi></mrow></msub></math>
https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=99951304&type=
https://html.publish.founderss.cn/rc-pub/api/common/picture?pictureId=99951292&type=
2.28600001
3.21733332
-differential privacy. The proposed framework systematically derives the theoretical relationships among identifiability
differential privacy
and mutual-information privacy
enabling a more precise estimation of privacy budget bounds. Furthermore
the framework provides a theoretical foundation for achieving privacy preservation in data-driven applications such as crowdsensing systems
location-based services
and large language models.
关键词
Keywords
references
OpenAI . Introducing ChatGPT [EB/OL ] . ( 2022-11-30 )[ 2024-10-23 ] . https://openai.com/index/chatgpt/ https://openai.com/index/chatgpt/ .
萝卜快跑 . 萝卜快跑: 自动驾驶出行服务平台 [EB/OL ] . ( 2024-06-10 )[ 2024-10-23 ] . https://www.robotgo.com https://www.robotgo.com .
APOLLO GO . Apollo Go: Autonomous driving travel service platform [EB/OL ] . ( 2024-06-10 )[ 2024-10-23 ] . https://www.robotgo.com https://www.robotgo.com . (in Chinese)
滴滴 . 滴滴一下 美好出行 [EB/OL ] . ( 2024-07-30 )[ 2024-10-23 ] . https://www.didiglobal.com https://www.didiglobal.com .
DIDI . DiDi-better travel [EB/OL ] . ( 2024-07-30 )[ 2024-10-23 ] . https://www.didiglobal.com https://www.didiglobal.com . (in Chinese)
赵景欣 , 岳星辉 , 冯崇朋 , 等 . 基于通用数据保护条例的数据隐私安全综述 [J ] . 计算机研究与发展 , 2022 , 59 ( 10 ): 2130 - 2163 .
ZHAO J X , YUE X H , FENG C P , et al . Survey of data privacy security based on general data protection regulation [J ] . Journal of Computer Research and Development , 2022 , 59 ( 10 ): 2130 - 2163 . (in Chinese)
刘雅辉 , 张铁赢 , 靳小龙 , 等 . 大数据时代的个人隐私保护 [J ] . 计算机研究与发展 , 2015 , 52 ( 1 ): 229 - 247 .
LIU Y H , ZHANG T Y , JIN X L , et al . Personal privacy protection in the era of big data [J ] . Journal of Computer Research and Development , 2015 , 52 ( 1 ): 229 - 247 . (in Chinese)
ZHENG Z R , LI Z T , JIANG H B , et al . Semantic-aware privacy-preserving online location trajectory data sharing [J ] . IEEE Transactions on Information Forensics and Security , 2022 , 17 : 2256 - 2271 .
ZHENG Z R , LI Z T , LI J , et al . Utility-aware and privacy-preserving trajectory synthesis model that resists social relationship privacy attacks [J ] . ACM Transactions on Intelligent Systems and Technology , 2022 , 13 ( 3 ): 1 - 28 .
ZHENG Z R , LI Z T , LONG S Q , et al . Pricing utility vs. location privacy: A differentially private data sharing framework for ride-on-demand services [J ] . IEEE Transactions on Dependable and Secure Computing , 2025 , 22 ( 4 ): 3497 - 3513 .
ZHENG Z R , LI Z T , HUANG C , et al . Defending data poisoning attacks in DP-based crowdsensing: A game-theoretic approach [J ] . IEEE Transactions on Mobile Computing , 2025 , 24 ( 3 ): 1859 - 1876 .
ZHENG Z R , LI Z T , HUANG C , et al . Data poisoning attacks and defenses to LDP-based privacy-preserving crowdsensing [J ] . IEEE Transactions on Dependable and Secure Computing , 2024 , 21 ( 5 ): 4861 - 4878 .
LI Z T , ZHENG Z R , GUO S M , et al . Disguised as privacy: Data poisoning attacks against differentially private crowdsensing systems [J ] . IEEE Transactions on Mobile Computing , 2023 , 22 ( 9 ): 5155 - 5169 .
邱宇 , 王持 , 齐开悦 , 等 . 智慧健康研究综述: 从云端到边缘的系统 [J ] . 计算机研究与发展 , 2020 , 57 ( 1 ): 53 - 73 .
QIU Y , WANG C , QI K Y , et al . A survey of smart health: System design from the cloud to the edge [J ] . Journal of Computer Research and Development , 2020 , 57 ( 1 ): 53 - 73 . (in Chinese)
Union European . Regulation (EU) 2016/679 of the European Parliament and of the Council [S ] . Luxembourg : Official Journal of the European Union , 2016 : 1 - 88 .
The Federal Council . Federal act on data protection [S/OL ] . ( 2023-09-01 )[ 2024-10-23 ] . https://www.fedlex.admin.ch/eli/cc/2022/491/en https://www.fedlex.admin.ch/eli/cc/2022/491/en .
全国人民代表大会 . 中华人民共和国网络安全法 [S/OL ] . ( 2016-11-07 )[ 2024-10-23 ] . http://www.npc.gov.cn/zgrdw/npc/xinwen/2016-11/07/content_2001605.htm http://www.npc.gov.cn/zgrdw/npc/xinwen/2016-11/07/content_2001605.htm .
National People’s Congress . Cybersecurity Law of the People’s Republic of China [S/OL ] . ( 2016-11-07 )[ 2024-10-23 ] . http://www.npc.gov.cn/zgrdw/npc/xinwen/2016-11/07/content_2001605.htm http://www.npc.gov.cn/zgrdw/npc/xinwen/2016-11/07/content_2001605.htm . (in Chinese)
全国人民代表大会 . 中华人民共和国个人信息保护法 [S/OL ] . ( 2021-08-20 )[ 2024-10-23 ] . http://www.npc.gov.cn/npc/c2/c30834/202108/t20210820_313088.html http://www.npc.gov.cn/npc/c2/c30834/202108/t20210820_313088.html .
National People’s Congress . Personal Information Protection Law of the People’s Republic of China [S/OL ] . ( 2021-08-20 )[ 2024-10-23 ] . http://www.npc.gov.cn/npc/c2/c30834/202108/t20210820_313088.html http://www.npc.gov.cn/npc/c2/c30834/202108/t20210820_313088.html . (in Chinese)
澎湃新闻 . 大批用户数据泄露,蔚来致歉 [EB/OL ] . ( 2022-12-21 )[ 2024-10-23 ] . https://www.thepaper.cn/newsDetail_forward_21269411 https://www.thepaper.cn/newsDetail_forward_21269411 .
The Paper . A large number of user data leaks, NIO apologizes [EB/OL ] . ( 2022-12-21 )[ 2024-10-23 ] . https://www.thepaper.cn/newsDetail_forward_21269411 https://www.thepaper.cn/newsDetail_forward_21269411 . (in Chinese)
澎湃新闻 . Meat偷传欧洲Facebook会员数据,被罚12亿欧元 [EB/OL ] . ( 2023-05-23 )[ 2024-10-23 ] . https://www.thepaper.cn/news Detail_forward_23188354 commTag=true https://www.thepaper.cn/newsDetail_forward_23188354commTag=true .
The Paper . Meat steals European Facebook membership data, fined 1.2 billion euros [EB/OL ] . ( 2023-05-23 )[ 2024-10-23 ] . https://www.thepaper.cn/news Detail_forward_23188354 commTag=true https://www.thepaper.cn/newsDetail_forward_23188354commTag=true . (in Chinese)
JIANG H B , LI J , ZHAO P , et al . Location privacy-preserving mechanisms in location-based services: A comprehensive survey [J ] . ACM Computing Surveys , 2021 , 54 ( 1 ): 3423165 .
康海燕 , 王骁识 . 基于数据特征相关性和自适应差分隐私的深度学习方法研究 [J ] . 电子学报 , 2024 , 52 ( 6 ): 1963 - 1976 .
KANG H Y , WANG X S . Research on the deep learning method based on data feature relevance and adaptive differential privacy [J ] . Acta Electronica Sinica , 2024 , 52 ( 6 ): 1963 - 1976 . (in Chinese)
曾卓 , 汪成亮 , 马飞 . 基于差分隐私的活动模式保护与时空轨迹发布方法 [J ] . 电子学报 , 2023 , 51 ( 3 ): 552 - 563 .
ZENG Z , WANG C L , MA F . Differentially private activity pattern and spatial-temporal trajectory publication [J ] . Acta Electronica Sinica , 2023 , 51 ( 3 ): 552 - 563 . (in Chinese)
蒋伟进 , 王海娟 , 周为 , 等 . 基于自适应连续时间的群智感知轨迹隐私保护方案 [J ] . 电子学报 , 2023 , 51 ( 10 ): 2894 - 2901 .
JIANG W J , WANG H J , ZHOU W , et al . Track privacy protection scheme based on adaptive continuous time in crowdsensing [J ] . Acta Electronica Sinica , 2023 , 51 ( 10 ): 2894 - 2901 . (in Chinese)
康海燕 , 冀源蕊 . 基于本地化差分隐私的时序位置发布方案研究 [J ] . 电子学报 , 2022 , 50 ( 9 ): 2222 - 2232 .
KANG H Y , JI Y R . Research on time-serial location data publication based on local differential privacy [J ] . Acta Electronica Sinica , 2022 , 50 ( 9 ): 2222 - 2232 . (in Chinese)
ZHAO P , JIANG H B , LI J , et al . Synthesizing privacy preserving traces: Enhancing plausibility with social networks [J ] . IEEE/ACM Transactions on Networking , 2019 , 27 ( 6 ): 2391 - 2404 .
LIU H , LI X H , LI H , et al . Spatiotemporal correlation-aware dummy-based privacy protection scheme for location-based services [C ] // IEEE INFOCOM 2017 - IEEE Conference on Computer Communications . Piscataway : IEEE , 2017 : 1 - 9 .
LEE J , CLIFTON C . Differential identifiability [C ] // Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining . New York : ACM , 2012 : 1041 - 1049 .
WANG W N , YING L , ZHANG J S . On the relation between identifiability, differential privacy, and mutual-information privacy [J ] . IEEE Transactions on Information Theory , 2016 , 62 ( 9 ): 5018 - 5029 .
DWORK C , MCSHERRY F , NISSIM K , et al . Calibrating noise to sensitivity in private data analysis [C ] // Theory of Cryptography . Berlin : Springer , 2006 : 265 - 284 .
DWORK C . Differential privacy [M ] // Automata, Languages and Programming . Berlin, Heidelberg : Springer , 2006 : 1 - 12 .
DUCHI J C , JORDAN M I , WAINWRIGHT M J . Local privacy and statistical minimax rates [C ] // Proceedings of the 2013 IEEE 54th Annual Symposium on Foundations of Computer Science . New York : ACM , 2013 : 429 - 438 .
SANKAR L , RAJAGOPALAN S R , POOR H V . Utility-privacy tradeoffs in databases: An information-theoretic approach [J ] . IEEE Transactions on Information Forensics and Security , 2013 , 8 ( 6 ): 838 - 852 .
CUFF P , YU L Q . Differential privacy as a mutual information constraint [C ] // Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security . New York : ACM , 2016 : 43 - 54 .
ANDRÉS M E , BORDENABE N E , CHATZIKOKOLAKIS K , et al . Geo-indistinguishability: Differential privacy for location-based systems [C ] // Proceedings of the 2013 ACM SIGSAC Conference on Computer & Communications Security . New York : ACM , 2013 : 901 - 914 .
SUN M , TAY W P . On the relationship between inference and data privacy in decentralized IoT networks [J ] . IEEE Transactions on Information Forensics and Security , 2020 , 15 : 852 - 866 .
BIAN M Y , HE G H , FENG G R , et al . Verifiable privacy-preserving heart rate estimation based on LSTM [J ] . IEEE Internet of Things Journal , 2024 , 11 ( 1 ): 1719 - 1731 .
KNORR K , ASPINALL D , WOLTERS M . On the privacy, security and safety of blood pressure and diabetes apps [C ] // ICT Systems Security and Privacy Protection . Cham : Springer , 2015 : 571 - 584 .
孙祯锋 . 运动员可穿戴设备中个人数据隐私的法律保护 [J ] . 沈阳体育学院学报 , 2022 , 41 ( 4 ): 104 - 110 .
SUN Z F . Legal protection of data privacy in athletes’ wearable devices [J ] . Journal of Shenyang Sport University , 2022 , 41 ( 4 ): 104 - 110 . (in Chinese)
张明武 , 黄嘉骏 , 韩亮 . 医疗大数据隐私保护多关键词范围搜索方案 [J ] . 软件学报 , 2021 , 32 ( 10 ): 3266 - 3282 .
ZHANG M W , HUANG J J , HAN L . Range-based multi-keyword searchable scheme with privacy protection in e-healthcare cloud systems [J ] . Journal of Software , 2021 , 32 ( 10 ): 3266 - 3282 . (in Chinese)
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