2 citations · 5 across the 3 of their papers we have counts for
4 papers
Privacy-Preserving Machine Learning in Untrusted Clouds Made Simple
Dayeol Lee, Dmitrii Kuvaiskii, Anjo Vahldiek-Oberwagner +1
We present a practical framework to deploy privacy-preserving machine learning (PPML) applications in untrusted clouds based on a trusted execution environment (TEE). Specifically,…
An Off-Chip Attack on Hardware Enclaves via the Memory Bus
Dayeol Lee, Dongha Jung, Ian T. Fang +2
This paper shows how an attacker can break the confidentiality of a hardware enclave with Membuster, an off-chip attack based on snooping the memory bus. An attacker with physical…
Keystone: An Open Framework for Architecting TEEs
Dayeol Lee, David Kohlbrenner, Shweta Shinde +2
Trusted execution environments (TEEs) are being used in all the devices from embedded sensors to cloud servers and encompass a range of cost, power constraints, and security threat…
Sanctorum: A lightweight security monitor for secure enclaves
Ilia Lebedev, Kyle Hogan, Jules Drean +5
Enclaves have emerged as a particularly compelling primitive to implement trusted execution environments: strongly isolated sensitive user-mode processes in a largely untrusted sof…