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20182025
most citedDifferentially Private Vertical Federated Clustering

20 citations · 54 across the 11 of their papers we have counts for

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5 papers · 1 filter

cs.CR2024

On the Robustness of LDP Protocols for Numerical Attributes under Data Poisoning Attacks

Xiaoguang Li, Zitao Li, Ninghui Li +1

Recent studies reveal that local differential privacy (LDP) protocols are vulnerable to data poisoning attacks where an attacker can manipulate the final estimate on the server by…

cs.CR2022★ 20 cited

Differentially Private Vertical Federated Clustering

Zitao Li, Tianhao Wang, Ninghui Li

In many applications, multiple parties have private data regarding the same set of users but on disjoint sets of attributes, and a server wants to leverage the data to train a mode…

cs.CR2019★ 6 cited

Estimating Numerical Distributions under Local Differential Privacy

Zitao Li, Tianhao Wang, Milan Lopuhaä-Zwakenberg +2

When collecting information, local differential privacy (LDP) relieves the concern of privacy leakage from users' perspective, as user's private information is randomized before se…

cs.CR2019

Improving Frequency Estimation under Local Differential Privacy

Milan Lopuhaä-Zwakenberg, Zitao Li, Boris Škorić +1

Local Differential Privacy protocols are stochastic protocols used in data aggregation when individual users do not trust the data aggregator with their private data. In such proto…

cs.CR2019

Locally Differentially Private Frequency Estimation with Consistency

Tianhao Wang, Milan Lopuhaä-Zwakenberg, Zitao Li +2

Local Differential Privacy (LDP) protects user privacy from the data collector. LDP protocols have been increasingly deployed in the industry. A basic building block is frequency o…