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A Framework for Subgraph Detection in Interdependent Networks via Graph Block-structured Optimization

Fei Jie, Chunpai Wang, Feng Chen, Lei Li, Xindong Wu
2020 IEEE Access  
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

Leman Akoglu, Hanghang Tong, Danai Koutra
2014 Data mining and knowledge discovery  
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]

Leman Akoglu and Hanghang Tong and Danai Koutra
2014 arXiv   pre-print
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

Stephen Ranshous, Shitian Shen, Danai Koutra, Steve Harenberg, Christos Faloutsos, Nagiza F. Samatova
2015 Wiley Interdisciplinary Reviews: Computational Statistics  
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