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Ninghui Li
Researcher at Purdue University
Publications - 266
Citations - 19897
Ninghui Li is an academic researcher from Purdue University. The author has contributed to research in topics: Access control & Differential privacy. The author has an hindex of 70, co-authored 262 publications receiving 17748 citations. Previous affiliations of Ninghui Li include New York University & National Chiao Tung University.
Papers
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Proceedings ArticleDOI
t-Closeness: Privacy Beyond k-Anonymity and l-Diversity
TL;DR: T-closeness as mentioned in this paper requires that the distribution of a sensitive attribute in any equivalence class is close to the distributions of the attribute in the overall table (i.e., the distance between the two distributions should be no more than a threshold t).
Proceedings ArticleDOI
Design of a role-based trust-management framework
TL;DR: The RT framework, a family of role-based trust management languages for representing policies and credentials in distributed authorization, is introduced, and the semantics of credentials are defined by presenting a translation from credentials to Datalog rules.
Journal ArticleDOI
Delegation logic: A logic-based approach to distributed authorization
TL;DR: D1LP provides a concept of proof-of-compliance that is founded on well-understood principles of logic programming and knowledge representation, and provides a logical framework for studying delegation.
Proceedings ArticleDOI
Using probabilistic generative models for ranking risks of Android apps
Hao Peng,Christopher Gates,Bhaskar P. Sarma,Ninghui Li,Yuan Qi,Rahul Potharaju,Cristina Nita-Rotaru,Ian M. Molloy +7 more
TL;DR: In this paper, the authors introduce the notion of risk scoring and risk ranking for Android apps, to improve risk communication for Android applications, and identify three desiderata for an effective risk scoring scheme.
Proceedings Article
Locally Differentially Private Protocols for Frequency Estimation
TL;DR: This paper introduces a framework that generalizes several LDP protocols proposed in the literature and yields a simple and fast aggregation algorithm, whose accuracy can be precisely analyzed, resulting in two new protocols that provide better utility than protocols previously proposed.