1 citations · 1 across the 6 of their papers we have counts for
6 papers
Hiding Directions, Leaking Structure: Breaking ArrowCloak through Low-Rank Structure
Beijie Liu, Junyi Ouyang, Haoxuan Xu +4
TEE-shielded inference keeps sensitive state in a trusted execution environment (TEE) while offloading linear algebra to an untrusted accelerator. Wang et al., in Game of Arrows (U…
Hollow-LLM Attack: Computationally Trivial Weights in Zero-Knowledge Verification of LLM Inference
Chen Gong, Beijie Liu, Mengyuan Li
As large language models (LLMs) grow in scale and are predominantly served from remote platforms, verifying faithful inference execution becomes critical (i.e., ensuring that a pro…
Query Cost Model Calibration in Confidential Virtual Machines
Qihan Zhang, Mengyuan Li, Ibrahim Sabek
With the growing adoption of Confidential Computing, running databases in confidential virtual machines (CVMs) such as AMD SEV-SNP has become an attractive way to protect sensitive…
OTRO: Oblivious Tokenization Path with Square-Root ORAM
Jonghyun Lee, Yongqin Wang, Rachit Rajat +3
The CPU-side large language model (LLM) tokenizer is a critical security gap in LLM serving through a confidential computing stack with CPU and GPU trusted execution environments (…
Ditto: Elastic Confidential VMs with Secure and Dynamic CPU Scaling
Shixuan Zhao, Mengyuan Li, Mengjia Yan +1
Confidential Virtual Machines (CVMs) are a type of VMbased Trusted Execution Environments (TEEs) designed to enhance the security of cloud-based VMs, safeguarding them even from ma…
Bridge the Future: High-Performance Networks in Confidential VMs without Trusted I/O devices
Mengyuan Li, Shashvat Srivastava, Mengjia Yan
Trusted I/O (TIO) is an appealing solution to improve I/O performance for confidential VMs (CVMs), with the potential to eliminate broad sources of I/O overhead. However, this pape…