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A Framework for Subgraph Detection in Interdependent Networks via Graph Block-structured Optimization
2020
IEEE Access
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It is common that real-world systems interact with each other. ...
Subgraph detection is useful in many fields, such as intrusion detection in computer networks [4] , [5] , disease outbreak detection [6] , event detection in activity networks [7] , [8] , and traffic ...
He is a Fellow of the IEEE and AAAS. ...
doi:10.1109/access.2020.3018497
fatcat:3kjiu4d7nnh4pba3b4il52v2gm
Graph based anomaly detection and description: a survey
2014
Data mining and knowledge discovery
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Detecting anomalies in data is a vital task, with numerous high-impact applications in areas such as security, finance, health care, and law enforcement. ...
We conclude our survey with a discussion on open theoretical and practical challenges in the field. 2 Leman Akoglu et al. ...
Essentially, a local statistic is computed for each time window, and the maximum statistic within each window is called scan statistic; if the scan statistic exceeds a threshold, the corresponding time ...
doi:10.1007/s10618-014-0365-y
fatcat:rfjn7bwdgra5faorwbdkkb45ze
Graph-based Anomaly Detection and Description: A Survey
[article]
2014
arXiv
pre-print
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As a key contribution, we provide a comprehensive exploration of both data mining and machine learning algorithms for these detection tasks. we give a general framework for the algorithms categorized under ...
Detecting anomalies in data is a vital task, with numerous high-impact applications in areas such as security, finance, health care, and law enforcement. ...
Essentially, a local statistic is computed for each time window, and the maximum statistic within each window is called scan statistic; if the scan statistic exceeds a threshold, the corresponding time ...
arXiv:1404.4679v2
fatcat:y6nsswymcfc2pa7qe7zrjzc7wq
Anomaly detection in dynamic networks: a survey
2015
Wiley Interdisciplinary Reviews: Computational Statistics
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Anomaly detection is an important problem with multiple applications, and thus has been studied for decades in various research domains. ...
In this survey, we aim to provide a comprehensive overview of anomaly detection in dynamic networks, concentrating on the state-of-the-art methods. ...
In addition, this material is based upon work supported in part with funding from the Laboratory for Analytic Sciences. ...
doi:10.1002/wics.1347
fatcat:44znvnsmlfcgfbbljcvmuubgpi