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Smart Active Sampling to enhance Quality Assurance Efficiency
We propose a new sampling strategy, called smart active sapling, for quality inspections outside the production line.
On the Usage of Generative Models for Network Anomaly Detection in Multivariate Time-Series
Despite the many attempts and approaches for anomaly detection explored over the years, the automatic detection of rare events in data communication networks remains a complex problem.
EXPLAIN-IT: Towards Explainable AI for Unsupervised Network Traffic Analysis
The application of unsupervised learning approaches, and in particular of clustering techniques, represents a powerful exploration means for the analysis of network measurements.
DeepMAL -- Deep Learning Models for Malware Traffic Detection and Classification
Robust network security systems are essential to prevent and mitigate the harming effects of the ever-growing occurrence of network attacks.
Two Decades of AI4NETS-AI/ML for Data Networks: Challenges & Research Directions
The popularity of Artificial Intelligence (AI) -- and of Machine Learning (ML) as an approach to AI, has dramatically increased in the last few years, due to its outstanding performance in various domains, notably in image, audio, and natural language processing.
