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Found 5 papers, 3 papers with code
Federated Analytics for 6G Networks: Applications, Challenges, and Opportunities
Extensive research is underway to meet the hyper-connectivity demands of 6G networks, driven by applications like XR/VR and holographic communications, which generate substantial data requiring network-based processing, transmission, and analysis.
General Phrase Debiaser: Debiasing Masked Language Models at a Multi-Token Level
The social biases and unwelcome stereotypes revealed by pretrained language models are becoming obstacles to their application.
LiPar: A Lightweight Parallel Learning Model for Practical In-Vehicle Network Intrusion Detection
Through experiments, we prove that LiPar has great detection performance, running efficiency, and lightweight model size, which can be well adapted to the in-vehicle environment practically and protect the in-vehicle CAN bus security.
Effective In-vehicle Intrusion Detection via Multi-view Statistical Graph Learning on CAN Messages
In this paper, we propose StatGraph: an Effective Multi-view Statistical Graph Learning Intrusion Detection to implement the fine-grained intrusion detection.
Towards Experienced Anomaly Detector through Reinforcement Learning
This abstract proposes a time series anomaly detector which 1) makes no assumption about the underlying mechanism of anomaly patterns, 2) refrains from the cumbersome work of threshold setting for good anomaly detection performance under specific scenarios, and 3) keeps evolving with the growth of anomaly detection experience.
