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20182023
most citedConfidential Machine Learning Computation in Untrusted Environments: A Systems Security Perspective

12 citations · 26 across the 5 of their papers we have counts for

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5 papers · 1 filter

cs.CR2023★ 8 cited

Capacity: Cryptographically-Enforced In-Process Capabilities for Modern ARM Architectures (Extended Version)

Kha Dinh Duy, Kyuwon Cho, Taehyun Noh +1

In-process compartmentalization and access control have been actively explored to provide in-place and efficient isolation of in-process security domains. Many works have proposed…

cs.CR2021★ 4 cited

PIM-Enclave: Bringing Confidential Computation Inside Memory

Kha Dinh Duy, Hojoon Lee

Demand for data-intensive workloads and confidential computing are the prominent research directions shaping the future of cloud computing. Computer architectures are evolving to a…

cs.CR2021★ 12 cited

Confidential Machine Learning Computation in Untrusted Environments: A Systems Security Perspective

Kha Dinh Duy, Taehyun Noh, Siwon Huh +1

As machine learning (ML) technologies and applications are rapidly changing many computing domains, security issues associated with ML are also emerging. In the domain of systems s…

cs.CR2018★ 1 cited

Rethinking Misalignment to Raise the Bar for Heap Pointer Corruption

Daehee Jang, Jonghwan Kim, Minjoon Park +3

Heap layout randomization renders a good portion of heap vulnerabilities unexploitable. However, some remnants of the vulnerabilities are still exploitable even under the randomize…

cs.CR2018★ 1 cited

Lord of the x86 Rings: A Portable User Mode Privilege Separation Architecture on x86

Hojoon Lee, Chihyun Song, Brent Byunghoon Kang

Modern applications are increasingly advanced and complex, and inevitably contain exploitable software bugs despite the ongoing efforts. The applications today often involve proces…