1 citations · 1 across the 7 of their papers we have counts for
5 papers · 1 filter
Dual Utilization of Perturbation for Stream Data Publication under Local Differential Privacy
Rong Du, Qingqing Ye, Yaxin Xiao +3
Stream data from real-time distributed systems such as IoT, tele-health, and crowdsourcing has become an important data source. However, the collection and analysis of user-generat…
Multi-class Item Mining under Local Differential Privacy
Yulian Mao, Qingqing Ye, Rong Du +3
Item mining, a fundamental task for collecting statistical data from users, has raised increasing privacy concerns. To address these concerns, local differential privacy (LDP) was…
Privacy for Free: Leveraging Local Differential Privacy Perturbed Data from Multiple Services
Rong Du, Qingqing Ye, Yue Fu +1
Local Differential Privacy (LDP) has emerged as a widely adopted privacy-preserving technique in modern data analytics, enabling users to share statistical insights while maintaini…
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…
Differential Aggregation against General Colluding Attackers
Rong Du, Qingqing Ye, Yue Fu +4
Local Differential Privacy (LDP) is now widely adopted in large-scale systems to collect and analyze sensitive data while preserving users' privacy. However, almost all LDP protoco…