Anomaly Detection in Modern Networks
Deadline for manuscript submissions: closed (15 April 2023) | Viewed by 7489
Interests: network management; network security; availability; 5G; NFV
Special Issues, Collections and Topics in MDPI journals
Anomaly detection is concerned with pinpointing data patterns that deviate from their expected behavior. This is a crucial research problem, due to its broad set of application domains, such as data analysis, cybersecurity, predictive maintenance, fault prevention, industrial automation, smart systems, and many others. In particular, anomaly detection problems are posing new challenges in the context of modern network architectures including: Cloud/Fog/Edge computing, Internet of Things (IoT), Network Function Virtualization (NFV), Software Defined Networking (SDN), Multi-access Edge Computing (MEC), and 5G/6G networks.
Due to the growing interest (both of academia and industry) in the anomaly detection field, for this Special Issue we encourage high-quality research contributions—both theoretical and experimental—and timely survey papers that pinpoint future research directions in this field.
Topics of interest include, but are not limited to, the following:
- Statistical approaches (e.g., time series analysis, signal processing techniques) for anomaly detection in modern networks;
- Machine Learning approaches for anomaly detection in modern networks;
- Novel algorithms for anomaly detection in modern networks;
- Privacy concerns related to the anomaly detection in modern networks;
- Applications of anomaly detection in modern networks;
- Industrial/Realistic case studies of anomaly detection in modern networks.
Dr. Mario Di Mauro
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