1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.CR2024
TEESlice: Protecting Sensitive Neural Network Models in Trusted Execution Environments When Attackers have Pre-Trained Models
Ding Li, Ziqi Zhang, Mengyu Yao +3
Trusted Execution Environments (TEE) are used to safeguard on-device models. However, directly employing TEEs to secure the entire DNN model is challenging due to the limited compu…
cs.CR2023★ 1 cited
No Privacy Left Outside: On the (In-)Security of TEE-Shielded DNN Partition for On-Device ML
Ziqi Zhang, Chen Gong, Yifeng Cai +5
On-device ML introduces new security challenges: DNN models become white-box accessible to device users. Based on white-box information, adversaries can conduct effective model ste…