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Secure and Efficient k-NN Queries.

, , , and . SEC, volume 502 of IFIP Advances in Information and Communication Technology, page 155-170. Springer, (2017)

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Secure and Efficient k-NN Queries., , , and . SEC, volume 502 of IFIP Advances in Information and Communication Technology, page 155-170. Springer, (2017)Differentially Private Outlier Detection in a Collaborative Environment., , , , and . Int. J. Cooperative Inf. Syst., 27 (3): 1850005:1-1850005:36 (2018)Identifying Anomalies While Preserving Privacy., , and . IEEE Trans. Knowl. Data Eng., 35 (12): 12264-12281 (December 2023)Preserving Missing Data Distribution in Synthetic Data., , and . WWW, page 2110-2121. ACM, (2023)Collaborative Differentially Private Outlier Detection for Categorical Data., , , , and . CIC, page 92-101. IEEE Computer Society, (2016)A Study of Users' Privacy Preferences for Data Sharing on Symptoms-Tracking/Health App., and . WPES@CCS, page 109-113. ACM, (2022)Intelligent Pandemic Surveillance via Privacy-Preserving Crowdsensing., , , , and . IEEE Intell. Syst., 37 (4): 88-96 (2022)A Privacy-Sensitive Collaborative Approach to Business Process Development., , , , , , , and . ICETE (Selected Papers), volume 585 of Communications in Computer and Information Science, page 318-342. Springer, (2015)How to Accurately and Privately Identify Anomalies., , and . ACM Conference on Computer and Communications Security, page 719-736. ACM, (2019)Privacy Attitudes and COVID Symptom Tracking Apps: Understanding Active Boundary Management by Users., , , , and . iConference (2), volume 13193 of Lecture Notes in Computer Science, page 332-346. Springer, (2022)