no code implementations • 10 Aug 2021 • Runhua Xu, Nathalie Baracaldo, James Joshi
In particular, existing PPML research cross-cut ML, systems and applications design, as well as security and privacy areas; hence, there is a critical need to understand state-of-the-art research, related challenges and a research roadmap for future research in PPML area.
no code implementations • 18 May 2021 • Leila Karimi, Mai Abdelhakim, James Joshi
In this paper, we propose an adaptive ABAC policy learning approach to automate the authorization management task.
no code implementations • 5 Mar 2021 • Runhua Xu, Nathalie Baracaldo, Yi Zhou, Ali Anwar, James Joshi, Heiko Ludwig
We empirically demonstrate the applicability for multiple types of ML models and show a reduction of 10%-70% of training time and 80% to 90% in data transfer with respect to the state-of-the-art approaches.
1 code implementation • 2 Feb 2021 • Runhua Xu, Chao Li, James Joshi
We also formally show the security guarantee provided by TAB, and analyze the privacy guarantee and trustworthiness it provides.
Cryptography and Security Networking and Internet Architecture
1 code implementation • 18 Dec 2020 • Runhua Xu, James Joshi, Chao Li
We propose a novel framework, NN-EMD, to train DNN over multiple encrypted datasets collected from multiple sources.
no code implementations • 16 Mar 2020 • Leila Karimi, Maryam Aldairi, James Joshi, Mai Abdelhakim
In this paper, we present a methodology for automatically learning ABAC policy rules from access logs of a system to simplify the policy development process.