Collecting and analyzing key-value data under shuffled differential privacy

Ning WANG , Wei ZHENG , Zhigang WANG , Zhiqiang WEI , Yu GU , Peng TANG , Ge YU

Front. Comput. Sci. ›› 2023, Vol. 17 ›› Issue (2) : 172606

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Front. Comput. Sci. ›› 2023, Vol. 17 ›› Issue (2) : 172606 DOI: 10.1007/s11704-022-1572-0
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Collecting and analyzing key-value data under shuffled differential privacy

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Ning WANG, Wei ZHENG, Zhigang WANG, Zhiqiang WEI, Yu GU, Peng TANG, Ge YU. Collecting and analyzing key-value data under shuffled differential privacy. Front. Comput. Sci., 2023, 17(2): 172606 DOI:10.1007/s11704-022-1572-0

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Balle B, Bell J, Gascón A, Nissim K. The privacy blanket of the shuffle model. In: Proceedings of the 39th Annual International Cryptology Conference on Advances in Cryptology. 2019, 638– 667

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Gu X, Li M, Cheng Y, Xiong L, Cao Y. PCKV: locally differentially private correlated key-value data collection with optimized utility. In: Proceedings of the 29th USENIX Conference on Security Symposium. 2020, 55

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Bittau A, Erlingsson Ú, Maniatis P, Mironov I, Raghunathan A, Lie D, Rudominer M, Kode U, Tinnes J, Seefeld B. Prochlo: strong privacy for analytics in the crowd. In: Proceedings of the 26th Symposium on Operating Systems Principles. 2017, 441– 459

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Wang S, Li J, Qian Y, Du J, Lin W, Yang W. Hiding numerical vectors in local private and shuffled messages. In: Proceedings of the 30th International Joint Conference on Artificial Intelligence. 2021, 3706– 3712

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