6 papers
PrivTuner with Homomorphic Encryption and LoRA: A P3EFT Scheme for Privacy-Preserving Parameter-Efficient Fine-Tuning of AI Foundation Models
Yang Li, Wenhan Yu, Jun Zhao
AI foundation models have recently demonstrated impressive capabilities across a wide range of tasks. Fine-tuning (FT) is a method of customizing a pre-trained AI foundation model…
QuHE: Optimizing Utility-Cost in Quantum Key Distribution and Homomorphic Encryption Enabled Secure Edge Computing Networks
Liangxin Qian, Yang Li, Jun Zhao
Ensuring secure and efficient data processing in mobile edge computing (MEC) systems is a critical challenge. While quantum key distribution (QKD) offers unconditionally secure key…
Private Transformer Inference in MLaaS: A Survey
Yang Li, Xinyu Zhou, Yitong Wang +2
Transformer models have revolutionized AI, powering applications like content generation and sentiment analysis. However, their deployment in Machine Learning as a Service (MLaaS)…
FedSem: A Resource Allocation Scheme for Federated Learning Assisted Semantic Communication
Xinyu Zhou, Yang Li, Jun Zhao
Semantic communication (SemCom), regarded as the evolution of the traditional Shannon's communication model, stresses the transmission of semantic information instead of the data i…
Resource Allocation for the Training of Image Semantic Communication Networks
Yang Li, Xinyu Zhou, Jun Zhao
Semantic communication is a new paradigm that aims at providing more efficient communication for the next-generation wireless network. It focuses on transmitting extracted, meaning…
A Survey on Private Transformer Inference
Yang Li, Xinyu Zhou, Yitong Wang +2
Transformer models have revolutionized AI, enabling applications like content generation and sentiment analysis. However, their use in Machine Learning as a Service (MLaaS) raises…