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20162022
most citedQuantifying Differential Privacy under Temporal Correlations

111 citations · 400 across the 24 of their papers we have counts for

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8 papers · 1 filter

cs.DB2020★ 1 cited

PANDA: Policy-aware Location Privacy for Epidemic Surveillance

Yang Cao, Shun Takagi, Yonghui Xiao +2

In this demonstration, we present a privacy-preserving epidemic surveillance system. Recently, many countries that suffer from coronavirus crises attempt to access citizen's locati…

cs.DB2019

Toward a view-based data cleaning architecture

Toshiyuki Shimizu, Hiroki Omori, Masatoshi Yoshikawa

Big data analysis has become an active area of study with the growth of machine learning techniques. To properly analyze data, it is important to maintain high-quality data. Thus,…

cs.DB2019★ 31 cited

Protecting Spatiotemporal Event Privacy in Continuous Location-Based Services

Yang Cao, Yonghui Xiao, Li Xiong +2

Location privacy-preserving mechanisms (LPPMs) have been extensively studied for protecting users' location privacy by releasing a perturbed location to third parties such as locat…

cs.DB2019★ 8 cited

When and where do you want to hide? Recommendation of location privacy preferences with local differential privacy

Maho Asada, Masatoshi Yoshikawa, Yang Cao

In recent years, it has become easy to obtain location information quite precisely. However, the acquisition of such information has risks such as individual identification and lea…

cs.DB2018★ 1 cited

Making View Update Strategies Programmable - Toward Controlling and Sharing Distributed Data -

Yasuhito Asano, Soichiro Hidaka, Zhenjiang Hu +10

Views are known mechanisms for controlling access of data and for sharing data of different schemas. Despite long and intensive research on views in both the database community and…

cs.DB2018★ 2 cited

A View-based Programmable Architecture for Controlling and Integrating Decentralized Data

Yasuhito Asano, Soichiro Hidaka, Zhenjiang Hu +9

The view and the view update are known mechanism for controlling access of data and for integrating data of different schemas. Despite intensive and long research on them in both t…

cs.DB2017★ 95 cited

Quantifying Differential Privacy in Continuous Data Release under Temporal Correlations

Yang Cao, Masatoshi Yoshikawa, Yonghui Xiao +1

Differential Privacy (DP) has received increasing attention as a rigorous privacy framework. Many existing studies employ traditional DP mechanisms (e.g., the Laplace mechanism) as…

cs.DB2016★ 111 cited

Quantifying Differential Privacy under Temporal Correlations

Yang Cao, Masatoshi Yoshikawa, Yonghui Xiao +1

Differential Privacy (DP) has received increased attention as a rigorous privacy framework. Existing studies employ traditional DP mechanisms (e.g., the Laplace mechanism) as primi…