A signal analysis of network traffic anomalies
Proceedings of the 2nd ACM SIGCOMM Workshop on Internet measurment
Diagnosing network-wide traffic anomalies
Proceedings of the 2004 conference on Applications, technologies, architectures, and protocols for computer communications
Mining anomalies using traffic feature distributions
Proceedings of the 2005 conference on Applications, technologies, architectures, and protocols for computer communications
Shrink: a tool for failure diagnosis in IP networks
Proceedings of the 2005 ACM SIGCOMM workshop on Mining network data
High breakdown estimators for principal components: the projection-pursuit approach revisited
Journal of Multivariate Analysis
Minerals: using data mining to detect router misconfigurations
Proceedings of the 2006 SIGCOMM workshop on Mining network data
IMC '05 Proceedings of the 5th ACM SIGCOMM conference on Internet Measurement
Combining filtering and statistical methods for anomaly detection
IMC '05 Proceedings of the 5th ACM SIGCOMM conference on Internet Measurement
IP fault localization via risk modeling
NSDI'05 Proceedings of the 2nd conference on Symposium on Networked Systems Design & Implementation - Volume 2
Diagnosing network disruptions with network-wide analysis
Proceedings of the 2007 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Sensitivity of PCA for traffic anomaly detection
Proceedings of the 2007 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Towards highly reliable enterprise network services via inference of multi-level dependencies
Proceedings of the 2007 conference on Applications, technologies, architectures, and protocols for computer communications
Answering what-if deployment and configuration questions with wise
Proceedings of the ACM SIGCOMM 2008 conference on Data communication
Troubleshooting chronic conditions in large IP networks
CoNEXT '08 Proceedings of the 2008 ACM CoNEXT Conference
Towards automated performance diagnosis in a large IPTV network
Proceedings of the ACM SIGCOMM 2009 conference on Data communication
Detailed diagnosis in enterprise networks
Proceedings of the ACM SIGCOMM 2009 conference on Data communication
Spatio-temporal compressive sensing and internet traffic matrices
Proceedings of the ACM SIGCOMM 2009 conference on Data communication
ANTIDOTE: understanding and defending against poisoning of anomaly detectors
Proceedings of the 9th ACM SIGCOMM conference on Internet measurement conference
URCA: pulling out anomalies by their root causes
INFOCOM'10 Proceedings of the 29th conference on Information communications
ASTUTE: detecting a different class of traffic anomalies
Proceedings of the ACM SIGCOMM 2010 conference
Detecting the performance impact of upgrades in large operational networks
Proceedings of the ACM SIGCOMM 2010 conference
Automating network application dependency discovery: experiences, limitations, and new solutions
OSDI'08 Proceedings of the 8th USENIX conference on Operating systems design and implementation
Listen to me if you can: tracking user experience of mobile network on social media
IMC '10 Proceedings of the 10th ACM SIGCOMM conference on Internet measurement
BasisDetect: a model-based network event detection framework
IMC '10 Proceedings of the 10th ACM SIGCOMM conference on Internet measurement
Automatic test packet generation
Proceedings of the 8th international conference on Emerging networking experiments and technologies
Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data
Root cause detection in a service-oriented architecture
Proceedings of the ACM SIGMETRICS/international conference on Measurement and modeling of computer systems
Robust assessment of changes in cellular networks
Proceedings of the ninth ACM conference on Emerging networking experiments and technologies
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Service quality in operational IP networks can be impacted due to planned or unplanned maintenance. During any maintenance activity, the responsibility of the operations team is to complete the work order and perform a check-up to ensure there are no unexpected service disruptions. Once the maintenance is complete, it is crucial to continuously monitor the network and look for any performance impacts. What operations lack today are effective tools to rapidly detect maintenance induced performance changes. The large scale and heterogeneity of network elements and performance metrics makes the problem extremely challenging. In this paper, we present PRISM, a new tool for detecting maintenance induced performance changes in a timely fashion. PRISM uses association between maintenance and the network elements to identify performance metrics for time-series analysis. It uses a new Multiscale Robust Local Subspace algorithm (MRLS) to accurately identify changes in performance even when the baseline is contaminated. We systematically evaluate PRISM using data collected at four large operational networks: a tier-1 backbone, VoIP, IPTV and 3G cellular and show that it achieves good accuracy. We also demonstrate the effectiveness of PRISM in real operational environments through interesting case study findings.