Publications (8)
PrivTune: Efficient and Privacy-Preserving Fine-Tuning of Large Language Models via Device-Cloud Collaboration
Yi Liu, Weixiang Han, Chengjun Cai +2
With the rise of large language models, service providers offer language models as a service, enabling users to fine-tune customized models via uploaded private datasets. However,…
Golden Grain: Building a Secure and Decentralized Model Marketplace for MLaaS
Jiasi Weng, Jian Weng, Chengjun Cai +2
ML-as-a-service (MLaaS) becomes increasingly popular and revolutionizes the lives of people. A natural requirement for MLaaS is, however, to provide highly accurate prediction serv…
ParaVul: A Parallel Large Language Model and Retrieval-Augmented Framework for Smart Contract Vulnerability Detection
Tenghui Huang, Jinbo Wen, Jiawen Kang +8
Smart contracts play a significant role in automating blockchain services. Nevertheless, vulnerabilities in smart contracts pose serious threats to blockchain security. Currently,…
Training with Differential Privacy: A Gradient-Preserving Noise Reduction Approach with Provable Security
Haodi Wang, Tangyu Jiang, Yu Guo +3
Deep learning models have been extensively adopted in various regions due to their ability to represent hierarchical features, which highly rely on the training set and procedures.…
Big2Small: A Unifying Neural Network Framework for Model Compression
Jing-Xiao Liao, Haoran Wang, Tao Li +4
With the development of foundational models, model compression has become a critical requirement. Various model compression approaches have been proposed such as low-rank decomposi…
Augmenting Encrypted Search: A Decentralized Service Realization with Enforced Execution
Shengshan Hu, Chengjun Cai, Qian Wang +4
Searchable symmetric encryption (SSE) allows the data owner to outsource an encrypted database to a remote server in a private manner while maintaining the ability for selectively…