Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Managing Communication Networks by Monitoring Databases
IEEE Transactions on Software Engineering
On the self-similar nature of Ethernet traffic (extended version)
IEEE/ACM Transactions on Networking (TON)
Graph identification techniques applied to network management problems
Graph identification techniques applied to network management problems
Decision-theoretic troubleshooting
Communications of the ACM
Intelligent detection for fault management of communication networks
Intelligent detection for fault management of communication networks
A Tractable Inference Algorithm for Diagnosing Multiple Diseases
UAI '89 Proceedings of the Fifth Annual Conference on Uncertainty in Artificial Intelligence
Fault isolation in multicast trees
Proceedings of the conference on Applications, Technologies, Architectures, and Protocols for Computer Communication
Characteristics of network traffic flow anomalies
IMW '01 Proceedings of the 1st ACM SIGCOMM Workshop on Internet Measurement
Statistical Detection of Enterprise NetworkProblems
Journal of Network and Systems Management
Adaptive Anomaly Detection in Transaction-Oriented Networks
Journal of Network and Systems Management
Intelligent Agents for Proactive Fault Detection
IEEE Internet Computing
A signal analysis of network traffic anomalies
Proceedings of the 2nd ACM SIGCOMM Workshop on Internet measurment
A Distributed and Reliable Platform for Adaptive Anomaly Detection in IP Networks
DSOM '99 Proceedings of the 10th IFIP/IEEE International Workshop on Distributed Systems: Operations and Management: Active Technologies for Network and Service Management
Sketch-based change detection: methods, evaluation, and applications
Proceedings of the 3rd ACM SIGCOMM conference on Internet measurement
Reliable Distributed Network Management by Replication
Journal of Network and Systems Management
Diagnosing network-wide traffic anomalies
Proceedings of the 2004 conference on Applications, technologies, architectures, and protocols for computer communications
Online identification of hierarchical heavy hitters: algorithms, evaluation, and applications
Proceedings of the 4th ACM SIGCOMM conference on Internet measurement
Probabilistic fault localization in communication systems using belief networks
IEEE/ACM Transactions on Networking (TON)
Detection and identification of network anomalies using sketch subspaces
Proceedings of the 6th ACM SIGCOMM conference on Internet measurement
Network protocol system monitoring: a formal approach with passive testing
IEEE/ACM Transactions on Networking (TON)
IMC '05 Proceedings of the 5th ACM SIGCOMM conference on Internet Measurement
Call Forwarding-Based Active Probing for POTS Fault Isolation
Journal of Network and Systems Management
Dynamic dependencies and performance improvement
LISA'08 Proceedings of the 22nd conference on Large installation system administration conference
Computer Networks: The International Journal of Computer and Telecommunications Networking
Bayesian networks to predict data mining algorithm behavior in ubiquitous computing environments
MSM'10/MUSE'10 Proceedings of the 2010 international conference on Analysis of social media and ubiquitous data
Automatic location detection system for anomaly traffic on wired/wireless networks
ICCSA'06 Proceedings of the 2006 international conference on Computational Science and Its Applications - Volume Part II
Application of Bayesian Networks for Autonomic Network Management
Journal of Network and Systems Management
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The increasing role of communication networks in today's society results in a demand for higher levels of network availability and reliability. At the same time, fault management is becoming more difficult due to the dynamic nature and heterogeneity of networks. We propose an intelligent monitoring system using adaptive statistical techniques. The system continually learns the normal behavior of the network and detects deviations from the norm. Within the monitoring system, the measurements are segmented, and features extracted from the segments are used to describe the behavior of the measurement variables. This information is combined in the structure of a Bayesian network. The proposed system is thereby able to detect unknown or unseen faults. Experimental results on real network data demonstrate that the proposed system can detect abnormal behavior before a fault actually occurs.