-
1
-
-
68049121093
-
Anomaly detection: A survey
-
Chandola V., Banerjee A., Kumar V., Anomaly detection: A survey, ACM Computing Surveys (CSUR); 41(3);2009; p. 15.
-
(2009)
ACM Computing Surveys (CSUR)
, vol.41
, Issue.3
, pp. 15
-
-
Chandola, V.1
Banerjee, A.2
Kumar, V.3
-
2
-
-
84880172566
-
Hybrid approach for detection of Anomaly network traffic using data mining techniques
-
Agarwal B., Mittal N., Hybrid Approach for Detection of Anomaly Network Traffic using Data Mining Techniques, Procedia Technology; 6; 2012; p. 996-1003.
-
(2012)
Procedia Technology
, vol.6
, pp. 996-1003
-
-
Agarwal, B.1
Mittal, N.2
-
3
-
-
84890509597
-
The survey of data mining applications and feature scope
-
Padhy N., Mishra P., Panigrahi R., The Survey of Data Mining Applications and Feature Scope; International Journal of Computer Science, Engineering and Information Technology (IJCSEIT), 2(3);2012; p. 43-58.
-
(2012)
International Journal of Computer Science, Engineering and Information Technology (IJCSEIT)
, vol.2
, Issue.3
, pp. 43-58
-
-
Padhy, N.1
Mishra, P.2
Panigrahi, R.3
-
5
-
-
0034455983
-
Adaptive intrusion detection: A data mining approach
-
Lee W., Stolfo S. J., Mok K. W., Adaptive intrusion detection: A data mining approach; Artificial Intelligence Review; 14(6);2000; p. 533-567.
-
(2000)
Artificial Intelligence Review
, vol.14
, Issue.6
, pp. 533-567
-
-
Lee, W.1
Stolfo, S.J.2
Mok, K.W.3
-
7
-
-
84893580396
-
Survey on data mining techniques in intrusion detection
-
Chauhan A., Mishra G., Kumar G., Survey on Data mining Techniques in Intrusion Detection; International Journal of Scientific & Engineering Research; 2(7), 2011; p. 1-4.
-
(2011)
International Journal of Scientific & Engineering Research
, vol.2
, Issue.7
, pp. 1-4
-
-
Chauhan, A.1
Mishra, G.2
Kumar, G.3
-
8
-
-
84896971289
-
A hierarchical framework using approximated local outlier factor for efficient Anomaly detection
-
Xu L., Yeh Y. R., Lee Y. J., Li J., A Hierarchical Framework Using Approximated Local Outlier Factor for Efficient Anomaly Detection; Procedia Computer Science; 19; 2013; p. 1174-1181.
-
(2013)
Procedia Computer Science
, vol.19
, pp. 1174-1181
-
-
Xu, L.1
Yeh, Y.R.2
Lee, Y.J.3
Li, J.4
-
10
-
-
76249095726
-
Traffic anomaly detection using k-means clustering
-
Munz, G., Li S., Carle G., Traffic Anomaly Detection Using K-Means Clustering; GI/ITG Workshop MMBnet; 2007; p. 1-8.
-
(2007)
GI/ITG Workshop MMBnet
, pp. 1-8
-
-
Munz, G.1
Li, S.2
Carle, G.3
-
11
-
-
84941094625
-
Data mining approaches for network intrusion detection from dimensionality reduction to misuse and anomaly detection
-
Syarif I., Prugel-Bennett A., Wills G., Data mining approaches for network intrusion detection from dimensionality reduction to misuse and anomaly detection; Journal of Information Technology Review; 3(2);2012; p. 70-83.
-
(2012)
Journal of Information Technology Review
, vol.3
, Issue.2
, pp. 70-83
-
-
Syarif, I.1
Prugel-Bennett, A.2
Wills, G.3
-
14
-
-
2942640996
-
Data mining for network intrusion detection
-
Dokas P., Ertoz L., Kumar V., Lazarevic A., Srivastava J., Tan P. N., Data mining for network intrusion detection, In Proceedings of NSF Workshop on Next Generation Data Mining; 2002; p. 21-30
-
(2002)
Proceedings of NSF Workshop on Next Generation Data Mining
, pp. 21-30
-
-
Dokas, P.1
Ertoz, L.2
Kumar, V.3
Lazarevic, A.4
Srivastava, J.5
Tan, P.N.6
-
15
-
-
57849130705
-
Anomaly-based network intrusion detection: Techniques, systems and challenges
-
Garcia-Teodoro P., Diaz-Verdejo J., Maciá-Fernández G., Vázquez E., Anomaly-based network intrusion detection: Techniques, systems and challenges; Computers and security; 28(1);2009; p. 18-28.
-
(2009)
Computers and Security
, vol.28
, Issue.1
, pp. 18-28
-
-
Garcia-Teodoro, P.1
Diaz-Verdejo, J.2
Maciá-Fernández, G.3
Vázquez, E.4
-
16
-
-
58349096877
-
Data mining-based intrusion detectors
-
Wu S. Y., Yen E., Data mining-based intrusion detectors; Expert Systems with Applications; 36(3);2009; p. 5605-5612.
-
(2009)
Expert Systems with Applications
, vol.36
, Issue.3
, pp. 5605-5612
-
-
Wu, S.Y.1
Yen, E.2
-
18
-
-
77954276704
-
Machine learning-based intrusion detection algorithm
-
Tang D. H., Cao Z., Machine Learning-based Intrusion Detection Algorithm; Journal of Computational Information Systems; 5(6);2009; p. 1825-1831.
-
(2009)
Journal of Computational Information Systems
, vol.5
, Issue.6
, pp. 1825-1831
-
-
Tang, D.H.1
Cao, Z.2
-
20
-
-
2942674608
-
Survey of fraud detection techniques
-
Kou Y., Lu C. T., Sirwongwattana S., Huang Y. P., Survey of fraud detection techniques; In Proceedings of the IEEE International conference Networking, sensing and control; 2; 2004; p. 749-754.
-
(2004)
Proceedings of the IEEE International Conference Networking, Sensing and Control
, vol.2
, pp. 749-754
-
-
Kou, Y.1
Lu, C.T.2
Sirwongwattana, S.3
Huang, Y.P.4
-
21
-
-
69249230890
-
Intrusion detection by machine learning: A review
-
Tsai C. F., Hsu Y. F., Lin C. Y., Lin W. Y., Intrusion detection by machine learning: A review; Expert Systems with Applications; 36(10);2009; p. 11994-12000.
-
(2009)
Expert Systems with Applications
, vol.36
, Issue.10
, pp. 11994-12000
-
-
Tsai, C.F.1
Hsu, Y.F.2
Lin, C.Y.3
Lin, W.Y.4
-
23
-
-
84872710120
-
A hybrid Anomaly detection framework in cloud computing using one-class and two-class support vector machines
-
Fu S., Liu J., Pannu H., A Hybrid Anomaly Detection Framework in Cloud Computing Using One-Class and Two-Class Support Vector Machines; In Advanced Data Mining and Applications; Springer Berlin Heidelberg; 2012; p. 726-738.
-
(2012)
Advanced Data Mining and Applications; Springer Berlin Heidelberg
, pp. 726-738
-
-
Fu, S.1
Liu, J.2
Pannu, H.3
-
24
-
-
77953620856
-
A novel unsupervised classification approach for network anomaly detection by k-Means clustering and ID3 decision tree learning methods
-
Yasami Y., Mozaffari S. P., A novel unsupervised classification approach for network anomaly detection by k-Means clustering and ID3 decision tree learning methods; The Journal of Supercomputing; 53(1);2010; p. 231-245.
-
(2010)
The Journal of Supercomputing
, vol.53
, Issue.1
, pp. 231-245
-
-
Yasami, Y.1
Mozaffari, S.P.2
-
25
-
-
77954276704
-
Machine learning-based intrusion detection algorithms
-
Tang D. H., Cao Z., Machine Learning-based Intrusion Detection Algorithms; Journal of Computational Information Systems; 5(6);2009; p. 1825-1831.
-
(2009)
Journal of Computational Information Systems
, vol.5
, Issue.6
, pp. 1825-1831
-
-
Tang, D.H.1
Cao, Z.2
-
28
-
-
33750514606
-
Modeling intrusion detection system using hybrid intelligent systems
-
Peddabachigari S., Abraham A., Grosan C, Thomas J., Modeling intrusion detection system using hybrid intelligent systems; Journal of network and computer applications; 30(1);2007; p. 114-132.
-
(2007)
Journal of Network and Computer Applications
, vol.30
, Issue.1
, pp. 114-132
-
-
Peddabachigari, S.1
Abraham, A.2
Grosan, C.3
Thomas, J.4
-
29
-
-
34250315640
-
An overview of anomaly detection techniques: Existing solutions and latest technological trends
-
Patcha A., Park J. M., An overview of anomaly detection techniques: Existing solutions and latest technological trends; Computer Networks; 51(12);2007; p. 3448-3470.
-
(2007)
Computer Networks
, vol.51
, Issue.12
, pp. 3448-3470
-
-
Patcha, A.1
Park, J.M.2
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