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Streaming Data Collection With a Private Sketch-Based Protocol

文献类型：期刊论文

作者Li, Ying1,2; Lee, Xiaodong1; Peng, Botao1; Palpanas, Themis3,4; Xue, Jingan5
刊名IEEE INTERNET OF THINGS JOURNAL
出版日期2024-08-01
卷号11期号:15页码:25950-25967
关键词Privacy Estimation Data collection Frequency estimation Protocols Protection Internet local differential privacy (LDP) mean estimation sketch
ISSN号2327-4662
DOI10.1109/JIOT.2024.3397908
英文摘要Data stream collection is critical to analyze service conditions and detect anomalies in time, especially in Internet of Things. However, it may undermine the individual privacy. Local differential privacy (LDP) has recently become a popular privacy-preserving technique protecting users' privacy. However, most of them are still limited to the assumption of one-item collection, resulting in poor utility when extended to the multi-item collection from a very large domain. This article proposes a private streaming data collection framework, private sketch-based framework (PSF), which takes advantage of sketches. Combining the proposed background information and a decode-first collection-side workflow, the framework improves the utility by reducing the errors introduced by the sketching algorithm and the privacy budget utilization when collecting multiple items. We analytically prove the superior accuracy and privacy characteristics of PSF. In order to support specific computing tasks, we build two private protocols based on PSF, PrivSketch and PrivSketch+, aiming at frequency estimation and mean estimation, respectively. We demonstrate the utility of PrivSketch and PrivSketch+ theoretically, and also evaluate them experimentally. Our evaluation, with several diverse synthetic and real data sets, demonstrates that PrivSketch is 1-3 orders of magnitude better than the competitors in terms of utility in both frequency estimation and frequent item estimation, while being up to similar to 100x faster. PrivSketch+ performs similar to 4 orders of magnitude better than advanced solutions, such as piecewise mechanism (PM) and hybrid mechanism (HM), under a limited privacy budget.
资助项目National Natural Science Foundation of China[62202450] ; Huawei[TC20201119008] ; Postdoctoral Exchange Program[YJ20210185]
WOS研究方向Computer Science ; Engineering ; Telecommunications
语种英语
WOS记录号WOS:001277988600083
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
源URL[http://119.78.100.204/handle/2XEOYT63/39627]  
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Lee, Xiaodong; Peng, Botao
作者单位1.Chinese Acad Sci, Inst Comp Technol, Lab Internet Infrastruct, Beijing 100190, Peoples R China
2.Univ Chinese Acad Sci, Sch Comp & Control Engn, Beijing 100190, Peoples R China
3.Univ Paris Cite, LIPADE, F-75006 Paris, France
4.French Univ Inst, F-75006 Paris, France
5.Huawei Technol, Cent Res Inst, Labs 2012, Shenzhen 518129, Peoples R China
推荐引用方式
GB/T 7714		 Li, Ying,Lee, Xiaodong,Peng, Botao,et al. Streaming Data Collection With a Private Sketch-Based Protocol[J]. IEEE INTERNET OF THINGS JOURNAL,2024,11(15):25950-25967.
APA Li, Ying,Lee, Xiaodong,Peng, Botao,Palpanas, Themis,&Xue, Jingan.(2024).Streaming Data Collection With a Private Sketch-Based Protocol.IEEE INTERNET OF THINGS JOURNAL,11(15),25950-25967.
MLA Li, Ying,et al."Streaming Data Collection With a Private Sketch-Based Protocol".IEEE INTERNET OF THINGS JOURNAL 11.15(2024):25950-25967.

入库方式： OAI收割

来源：计算技术研究所

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