2 papers
cs.CR2026
Breaking Euston: Recovering Private Inputs from Secure Inference by Exploiting Subspace Leakage
Jiaqi Zhao, Fengwei Wang
In the 47th IEEE Symposium on Security and Privacy (IEEE S&P 2026), Gao et al. proposed an efficient and user-friendly secure transformer inference framework, namely Euston. In Eus…
cs.LG2025
DPFNAS: Differential Privacy-Enhanced Federated Neural Architecture Search for 6G Edge Intelligence
Yang Lv, Jin Cao, Ben Niu +4
The Sixth-Generation (6G) network envisions pervasive artificial intelligence (AI) as a core goal, enabled by edge intelligence through on-device data utilization. To realize this…