36 citations · 38 across the 31 of their papers we have counts for
5 papers · 1 filter
Data Poisoning Attacks to Local Differential Privacy Protocols for Graphs
Xi He, Kai Huang, Qingqing Ye +1
Graph analysis has become increasingly popular with the prevalence of big data and machine learning. Traditional graph data analysis methods often assume the existence of a trusted…
PriPL-Tree: Accurate Range Query for Arbitrary Distribution under Local Differential Privacy
Leixia Wang, Qingqing Ye, Haibo Hu +1
Answering range queries in the context of Local Differential Privacy (LDP) is a widely studied problem in Online Analytical Processing (OLAP). Existing LDP solutions all assume a u…
PrivShape: Extracting Shapes in Time Series under User-Level Local Differential Privacy
Yulian Mao, Qingqing Ye, Haibo Hu +2
Time series have numerous applications in finance, healthcare, IoT, and smart city. In many of these applications, time series typically contain personal data, so privacy infringem…
Interactive Trimming against Evasive Online Data Manipulation Attacks: A Game-Theoretic Approach
Yue Fu, Qingqing Ye, Rong Du +1
With the exponential growth of data and its crucial impact on our lives and decision-making, the integrity of data has become a significant concern. Malicious data poisoning attack…
LDPRecover: Recovering Frequencies from Poisoning Attacks against Local Differential Privacy
Xinyue Sun, Qingqing Ye, Haibo Hu +4
Local differential privacy (LDP), which enables an untrusted server to collect aggregated statistics from distributed users while protecting the privacy of those users, has been wi…