3 accepted papers
Network traffic analysis is crucial for maintaining the security of networks. Yet deploying accurate models on edge nodes remains challenging due to protocol diversity, complex traffic behaviors, and stringent resource constraints. Although recent deep learning models achieve strong performance, the
The combination of self-supervised learning and adversarial training (AT) can significantly improve the adversarial robustness of self-supervised models. However, the robustness of self-supervised adversarial training (self-AT) still lags behind that of state-of-the-art (SOTA) supervised AT (sup-AT)…
The ever-increasing complexity and scale of 5G communication networks pose huge challenges to network operations. Root cause analysis is considered as a promising method for fault detection. However, it still suffers challenges of severely uneven distribution of fault data, low accuracy in root caus…