Network Anomaly Detection System: The State of Art of Network Behaviour Analysis
ICHIT '08 Proceedings of the 2008 International Conference on Convergence and Hybrid Information Technology
Network anomaly detection and classification via opportunistic sampling
IEEE Network: The Magazine of Global Internetworking - Special issue title on recent developments in network intrusion detection
Fast traffic anomalies detection using SNMP MIB correlation analysis
ICACT'09 Proceedings of the 11th international conference on Advanced Communication Technology - Volume 1
Computer Networking for LANs to WANs: Hardware, Software and Security
Computer Networking for LANs to WANs: Hardware, Software and Security
Network anomaly confirmation, diagnosis and remediation
Allerton'09 Proceedings of the 47th annual Allerton conference on Communication, control, and computing
Computer Networks: The International Journal of Computer and Telecommunications Networking
Predictive network anomaly detection and visualization
IEEE Transactions on Information Forensics and Security
Histogram-based traffic anomaly detection
IEEE Transactions on Network and Service Management
A survey of resilience differentiation frameworks in communication networks
IEEE Communications Surveys & Tutorials
A Survey on Internet Traffic Identification
IEEE Communications Surveys & Tutorials
Intrusion analysis with deep packet inspection: Increasing efficiency of packet based investigations
CSC '11 Proceedings of the 2011 International Conference on Cloud and Service Computing
Hi-index | 0.00 |
Systematic network monitoring can be the cornerstone for the dependable operation of safety-critical distributed systems. In this paper, we present our vision for informed anomaly detection through network monitoring and resilience measurements to increase the operators' visibility of ATM communication networks. We raise the question of how to determine the optimal level of automation in this safety-critical context, and we present a novel passive network monitoring system that can reveal network utilisation trends and traffic patterns in diverse timescales. Using network measurements, we derive resilience metrics and visualisations to enhance the operators' knowledge of the network and traffic behaviour, and allow for network planning and provisioning based on informed what-if analysis.