S3 Lab - Software & Systems Security Laboratory
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AI Vault

The AI Vault project designs and develops a new trusted execution environment (TEE) tailored to run artificial intelligence (AI) and machine learning (ML) programs on modern AI platforms (e.g., cloud and embedded devices) while providing strong data confidentiality and high efficiency.

TEE technologies, such as Intel SGX and ARM TrustZone, provide strong security guarantees against powerful attacks. However, due to the data-intensive characteristics of AI/ML programs and limitations of TEE, it is challenging to protect AI/ML programs using TEE technologies without sacrificing security and/or performance significantly. The goal of this project is to overcome these challenges to practically enable trusted AI and ML execution on AI platforms in production.

Recent News

Available Work

  • Vessels: a deep learning framework for confidential prediction using Intel SGX (paper)

Ongoing Work

  • Photon
  • MLSide
  • T-Slices



Vessels: Efficient and Scalable Deep Learning Prediction on Trusted Processors
Kyungtae Kim, Chung Hwan Kim, John Junghwan Rhee, Xiao Yu, Haifeng Chen, Dave (Jing) Tian, and Byoungyoung Lee
In SOCC 2020 [ pdf :: slides :: bibtex ]