activity
20092023
most citedMembership Inference Attacks and Defenses in Classification Models

63 citations · 279 across the 28 of their papers we have counts for

collaborators

28 papers

cs.CR2023★ 1 cited

PolyScope: Multi-Policy Access Control Analysis to Triage Android Scoped Storage

Yu-Tsung Lee, Haining Chen, William Enck +5

Android's filesystem access control is a crucial aspect of its system integrity. It utilizes a combination of mandatory access controls, such as SELinux, and discretionary access c…

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.CR2022★ 7 cited

Fine-grained Poisoning Attack to Local Differential Privacy Protocols for Mean and Variance Estimation

Xiaoguang Li, Ninghui Li, Wenhai Sun +2

Although local differential privacy (LDP) protects individual users' data from inference by an untrusted data curator, recent studies show that an attacker can launch a data poison…

cs.CR2022★ 9 cited

Using Illustrations to Communicate Differential Privacy Trust Models: An Investigation of Users' Comprehension, Perception, and Data Sharing Decision

Aiping Xiong, Chuhao Wu, Tianhao Wang +4

Proper communication is key to the adoption and implementation of differential privacy (DP). However, a prior study found that laypeople did not understand the data perturbation pr…

cs.CR2022★ 20 cited

Are Your Sensitive Attributes Private? Novel Model Inversion Attribute Inference Attacks on Classification Models

Shagufta Mehnaz, Sayanton V. Dibbo, Ehsanul Kabir +2

Increasing use of machine learning (ML) technologies in privacy-sensitive domains such as medical diagnoses, lifestyle predictions, and business decisions highlights the need to be…

cs.CR2021★ 1 cited

DPSyn: Experiences in the NIST Differential Privacy Data Synthesis Challenges

Ninghui Li, Zhikun Zhang, Tianhao Wang

We summarize the experience of participating in two differential privacy competitions organized by the National Institute of Standards and Technology (NIST). In this paper, we docu…