8 citations · 9 across the 6 of their papers we have counts for
6 papers
DEFENDCLI: {Command-Line} Driven Attack Provenance Examination
Peilun Wu, Nan Sun, Nour Moustafa +2
Endpoint Detection and Response (EDR) solutions embrace the method of attack provenance graph to discover unknown threats through system event correlation. However, this method sti…
Privacy Meets Explainability: Managing Confidential Data and Transparency Policies in LLM-Empowered Science
Yashothara Shanmugarasa, Shidong Pan, Ming Ding +2
As Large Language Models (LLMs) become integral to scientific workflows, concerns over the confidentiality and ethical handling of confidential data have emerged. This paper explor…
Unique Security and Privacy Threats of Large Language Models: A Comprehensive Survey
Shang Wang, Tianqing Zhu, Bo Liu +4
With the rapid development of artificial intelligence, large language models (LLMs) have made remarkable advancements in natural language processing. These models are trained on va…
Energy-Efficient Wireless Federated Learning via Doubly Adaptive Quantization
Xuefeng Han, Wen Chen, Jun Li +5
Federated learning (FL) has been recognized as a viable distributed learning paradigm for training a machine learning model across distributed clients without uploading raw data. H…
Reconfigurable Intelligent Surface Aided Space Shift Keying With Imperfect CSI
Xusheng Zhu, Wen Chen, Qingqing Wu +4
In this paper, we investigate the performance of reconfigurable intelligent surface (RIS)-aided spatial shift keying (SSK) wireless communication systems with imperfect channel sta…
Federated Meta-Learning for Few-Shot Fault Diagnosis with Representation Encoding
Jixuan Cui, Jun Li, Zhen Mei +5
Deep learning-based fault diagnosis (FD) approaches require a large amount of training data, which are difficult to obtain since they are located across different entities. Federat…