8 papers
Disentangling Multi-View Scanning in Mamba for Network Traffic Anomaly Detection
Xinglin Lian, Chengtai Cao, Ting Zhong +1
Network Traffic Anomaly Detection (NTAD) is a critical task in cybersecurity, yet timely and accurate anomaly detection remains challenging. Mamba has emerged as a particularly pro…
AOEPT: Breaking the Implicit Modality-Reduction Bottleneck in Modality-Missing Prompt Tuning
Jian Lang, Rongpei Hong, Ting Zhong +1
Deploying multimodal systems in real-world environments often entails handling modality-missing scenarios, where one or more modalities are unavailable. While recent studies addres…
Decompose to Understand, Fuse to Detect: Frequency-Decoupled Anomaly Detection for Encrypted Network Traffic
Xinglin Lian, Chengtai Cao, Ting Zhong +3
Network traffic anomaly detection represents a critical cybersecurity task, yet widespread encryption makes this task increasingly challenging. In response, image-based methods tha…
Shedding the Facades, Connecting the Domains: Detecting Shifting Multimodal Hate Video with Test-Time Adaptation
Jiao Li, Jian Lang, Xikai Tang +6
Hate Video Detection (HVD) is crucial for online ecosystems. Existing methods assume identical distributions between training (source) and inference (target) data. However, hateful…
Modality-Balanced Collaborative Distillation for Multi-Modal Domain Generalization
Xiaohan Wang, Zhangtao Cheng, Ting Zhong +2
Weight Averaging (WA) has emerged as a powerful technique for enhancing generalization by promoting convergence to a flat loss landscape, which correlates with stronger out-of-dist…
Nip Rumors in the Bud: Retrieval-Guided Topic-Level Adaptation for Test-Time Fake News Video Detection
Jian Lang, Rongpei Hong, Ting Zhong +2
Fake News Video Detection (FNVD) is critical for social stability. Existing methods typically assume consistent news topic distribution between training and test phases, failing to…