Differential Privacy under Continual Observation

doi:10.13328/j.cnki.jos.006042

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Home > Archive>Volume 31, Issue 6, 2020 >1761-1785. DOI:10.13328/j.cnki.jos.006042

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Differential Privacy under Continual Observation
DOI:
                        10.13328/j.cnki.jos.006042
                    
Author:
                        LIANG Wen-JuanLIANG Wen-Juan
Key Laboratory of Data Engineering and Knowledge of the Ministry of Education (Renmin University of China), Beijing 100872, China;School of Information, Renmin University of China, Beijing 100872, China;School of Computer and Information Engineering, Henan University, Kaifeng 475001, China
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CHEN HongCHEN Hong
Key Laboratory of Data Engineering and Knowledge of the Ministry of Education (Renmin University of China), Beijing 100872, China;School of Information, Renmin University of China, Beijing 100872, China
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WU Yun-ChengWU Yun-Cheng
Key Laboratory of Data Engineering and Knowledge of the Ministry of Education (Renmin University of China), Beijing 100872, China;School of Information, Renmin University of China, Beijing 100872, China
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ZHAO DanZHAO Dan
Key Laboratory of Data Engineering and Knowledge of the Ministry of Education (Renmin University of China), Beijing 100872, China;School of Information, Renmin University of China, Beijing 100872, China
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LI Cui-PingLI Cui-Ping
Key Laboratory of Data Engineering and Knowledge of the Ministry of Education (Renmin University of China), Beijing 100872, China;School of Information, Renmin University of China, Beijing 100872, China
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Fund Project:National Natural Science Foundation of China (61532021, 61772537, 61772536, 61702522)

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Abstract:

With the development of information technologies and Internet of things (IoT) technologies,there are more and more scenarios under continual monitoring, such as transportation monitoring, disease monitoring, smart infrastructure etc. In these scenarios, how to protect the privacy of continuous sharing data is facing major challenges. Differential privacy is arigorous and provable privacy definition. Earlier research on differential privacy has focused on “one-shot” release on a static dataset. However, differential privacy under continual observation focuses on the continuous computationon the dynamic dataset. Now it has become one of the research hotspots. This study surveys the state-of-the-art techniqueson differential privacy under continual observation, and focuses on summarizing existing schemes that provide event-levelprivacy, user-levelprivacy, and w-event privacy. Following a comprehensive comparison and analysis of existing techniques, further research prospectsare put forward.

Key words:differential privacy|continual monitoring|event-level privacy|user-level privacy|w-event privacy

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梁文娟,陈红,吴云乘,赵丹,李翠平.持续监控下差分隐私保护.软件学报,2020,31(6):1761-1785

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Received:July 06,2018
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Online: April 21,2020
Published: June 06,2020

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