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Anomaly detection
Known as:
Anomaly
, Deviation detection
, Exception detection
In data mining, anomaly detection (also outlier detection) is the identification of items, events or observations which do not conform to an expected…
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Related topics
Related topics
32 relations
Artificial immune system
Association rule learning
Cluster analysis
Computer forensics
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Broader (2)
Data mining
Data security
Papers overview
Semantic Scholar uses AI to extract papers important to this topic.
Review
2019
Review
2019
Deep Learning for Anomaly Detection: A Survey
Raghavendra Chalapathy University of Sydney
,
Capital Markets Cooperative Research Centre
,
Sanjay Chawla Qatar Computing Research Institute
,
Hbku
2019
Corpus ID: 57825713
Anomaly detection is an important problem that has been well-studied within diverse research areas and application domains. The…
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Review
2014
Review
2014
Network Anomaly Detection: Methods, Systems and Tools
M. Bhuyan
,
D. Bhattacharyya
,
J. Kalita
IEEE Communications Surveys and Tutorials
2014
Corpus ID: 4937576
Network anomaly detection is an important and dynamic research area. Many network intrusion detection methods and systems (NIDS…
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Highly Cited
2012
Highly Cited
2012
Isolation-Based Anomaly Detection
F. Liu
,
K. Ting
,
Zhi-Hua Zhou
TKDD
2012
Corpus ID: 207193045
Anomalies are data points that are few and different. As a result of these properties, we show that, anomalies are susceptible to…
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Highly Cited
2010
Highly Cited
2010
Anomaly detection in crowded scenes
V. Mahadevan
,
Weixin Li
,
V. Bhalodia
,
N. Vasconcelos
IEEE Computer Society Conference on Computer…
2010
Corpus ID: 206591190
A novel framework for anomaly detection in crowded scenes is presented. Three properties are identified as important for the…
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Review
2009
Review
2009
Anomaly detection: A survey
V. Chandola
,
A. Banerjee
,
Vipin Kumar
CSUR
2009
Corpus ID: 207172599
Anomaly detection is an important problem that has been researched within diverse research areas and application domains. Many…
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Review
2003
Review
2003
Anomaly detection in IP networks
M. Thottan
,
C. Ji
IEEE Transactions on Signal Processing
2003
Corpus ID: 18144675
Network anomaly detection is a vibrant research area. Researchers have approached this problem using various techniques such as…
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Highly Cited
2003
Highly Cited
2003
Anomaly detection of web-based attacks
Christopher Krügel
,
Giovanni Vigna
Conference on Computer and Communications…
2003
Corpus ID: 5856351
Web-based vulnerabilities represent a substantial portion of the security exposures of computer networks. In order to detect…
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Highly Cited
2003
Highly Cited
2003
A Comparative Study of Anomaly Detection Schemes in Network Intrusion Detection
A. Lazarevic
,
Levent Ertöz
,
Vipin Kumar
,
Aysel Ozgur
,
J. Srivastava
SDM
2003
Corpus ID: 2470919
Intrusion detection corresponds to a suite of techniques that are used to identify attacks against computers and network…
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Highly Cited
2002
Highly Cited
2002
Anomaly detection from hyperspectral imagery
D. Stein
,
S. Beaven
,
L. Hoff
,
E. M. Winter
,
A. Schaum
,
A. Stocker
IEEE Signal Processing Magazine
2002
Corpus ID: 120317272
We develop anomaly detectors, i.e., detectors that do not presuppose a signature model of one or more dimensions, for three…
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Highly Cited
2002
Highly Cited
2002
A Geometric Framework for Unsupervised Anomaly Detection
E. Eskin
,
Andrew O. Arnold
,
M. Prerau
,
Leonid Portnoy
,
S. Stolfo
Applications of Data Mining in Computer Security
2002
Corpus ID: 61058940
Most current intrusion detection systems employ signature-based methods or data mining-based methods which rely on labeled…
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