189 citations · 197 across the 11 of their papers we have counts for
11 papers
SGX-MR-Prot: Efficient and Developer-Friendly Access-Pattern Protection in Trusted Execution Environments
AKM Mubashwir Alam, Justin Boyce, Keke Chen
Trusted Execution Environments, such as Intel SGX, use hardware supports to ensure the confidentiality and integrity of applications against a compromised cloud system. However, si…
Making Your Program Oblivious: a Comparative Study for Side-channel-safe Confidential Computing
AKM Mubashwir Alam, Keke Chen
Trusted Execution Environments (TEEs) are gradually adopted by major cloud providers, offering a practical option of \emph{confidential computing} for users who don't fully trust p…
A Comparative Study of Image Disguising Methods for Confidential Outsourced Learning
Sagar Sharma, Yuechun Gu, Keke Chen
Large training data and expensive model tweaking are standard features of deep learning for images. As a result, data owners often utilize cloud resources to develop large-scale co…
Confidential High-Performance Computing in the Public Cloud
Keke Chen
High-Performance Computing (HPC) in the public cloud democratizes the supercomputing power that most users cannot afford to purchase and maintain. Researchers have studied its viab…
Confidential Machine Learning on Untrusted Platforms: A Survey
Sagar Sharma, Keke Chen
With the ever-growing data and the need for developing powerful machine learning models, data owners increasingly depend on various untrusted platforms (e.g., public clouds, edges,…
SGX-MR: Regulating Dataflows for Protecting Access Patterns of Data-Intensive SGX Applications
A K M Mubashwir Alam, Sagar Sharma, Keke Chen
Intel SGX has been a popular trusted execution environment (TEE) for protecting the integrity and confidentiality of applications running on untrusted platforms such as cloud. Howe…