-
2
-
-
84874176711
-
-
KDD Cup, 1999. http://kdd.ics.uci.edu/databases/kddcup99/kddcup99.html.
-
(1999)
-
-
-
3
-
-
0038324535
-
-
chapter A geometric framework for unsupervised anomaly detection: detecting intrusions in unlabeled data. Kluwer
-
E. Eskin, A. Arnold, M. Prerau, L. Portnoy, and S. Stolfo. Applications of Data Mining in Computer Security, chapter A geometric framework for unsupervised anomaly detection: detecting intrusions in unlabeled data. Kluwer, 2002.
-
(2002)
Applications of Data Mining in Computer Security
-
-
Eskin, E.1
Arnold, A.2
Prerau, M.3
Portnoy, L.4
Stolfo, S.5
-
4
-
-
33745561205
-
An introduction to variable and feature selection
-
I. Guyon and A. Elisseeff. An Introduction to Variable and Feature Selection. JMLR, 3:1157-1182, 2003.
-
(2003)
JMLR
, vol.3
, pp. 1157-1182
-
-
Guyon, I.1
Elisseeff, A.2
-
5
-
-
85042797742
-
Learning program behavior profiles for intrusion detection
-
Santa Clara, USA, April
-
A. K. Ghosh, A. Schwartzbard, and M. Schatz. Learning Program Behavior Profiles for Intrusion Detection. In Proc. of the 1st USENIX Workshop on Intrusion Detection and Network Monitoring, pages 51-62, Santa Clara, USA, April 1999. http://www.cigital.com/papers/download/usenix-id99.pdf.
-
(1999)
Proc. of the 1st USENIX Workshop on Intrusion Detection and Network Monitoring
, pp. 51-62
-
-
Ghosh, A.K.1
Schwartzbard, A.2
Schatz, M.3
-
6
-
-
24744463914
-
Results of the DARPA 1998 offline intrusion detection evaluation
-
R. Lippmann, R. K. Cunningham, D. J. Fried, K. R. Kendall, S. E. Webster, and M. A. Zissman. Results of the DARPA 1998 Offline Intrusion Detection Evaluation. In Proc. RAID 1999, 1999. http://www.ll.mit.edu/IST/ideval/pubs/ 1999/RAID-1999a.pdf.
-
(1999)
Proc. RAID 1999
-
-
Lippmann, R.1
Cunningham, R.K.2
Fried, D.J.3
Kendall, K.R.4
Webster, S.E.5
Zissman, M.A.6
-
7
-
-
84885774862
-
A framework for constructing features and models for intrusion detection systems
-
November
-
W. Lee and S. Stolfo. A Framework for Constructing Features and Models for Intrusion Detection Systems. In ACM Transactions on Information and System Security, volume 3, pages 227-261, November 2001.
-
(2001)
ACM Transactions on Information and System Security
, vol.3
, pp. 227-261
-
-
Lee, W.1
Stolfo, S.2
-
8
-
-
85016684916
-
Intrusion detection in unlabeled data with quarter-sphere Support Vector Machines
-
P. Laskov, C. Schäfer, and I. Kotenko. Intrusion detection in unlabeled data with quarter-sphere Support Vector Machines. In Proc. DIMVA, pages 71-82, 2004.
-
(2004)
Proc. DIMVA
, pp. 71-82
-
-
Laskov, P.1
Schäfer, C.2
Kotenko, I.3
-
9
-
-
33745162710
-
Intrusion detection in unlabeled data with quarter-sphere Support Vector Machines (Extended Version)
-
P. Laskov, C. Schäfer, I. Kotenko, and K.-R. Müller. Intrusion detection in unlabeled data with quarter-sphere Support Vector Machines (Extended Version). Praxis der Informationsverarbeitung und Kommunikation, 27:228-236, 2004.
-
(2004)
Praxis der Informationsverarbeitung und Kommunikation
, vol.27
, pp. 228-236
-
-
Laskov, P.1
Schäfer, C.2
Kotenko, I.3
Müller, K.-R.4
-
12
-
-
0035272287
-
An introduction to kernel-based learning algorithms
-
K.-R. Müller, S. Mika, G. Rätsch, K. Tsuda, and B. Schölkopf. An Introduction to Kernel-Based Learning Algorithms. IEEE Transactions on Neural Networks, 12(2):181-201, 2001.
-
(2001)
IEEE Transactions on Neural Networks
, vol.12
, Issue.2
, pp. 181-201
-
-
Müller, K.-R.1
Mika, S.2
Rätsch, G.3
Tsuda, K.4
Schölkopf, B.5
-
13
-
-
85084164413
-
Bro: A system for detecting network intruders in real-time
-
V. Paxson. Bro: a system for detecting network intruders in real-time. In Proc. USENIX Security Symposium, pages 31-51, 1998.
-
(1998)
Proc. USENIX Security Symposium
, pp. 31-51
-
-
Paxson, V.1
-
14
-
-
72949121678
-
-
Lawrence Berkeley National Laboratroy and ICSI Center for Internet Research
-
V. Paxson. The Bro 0.8 User Manual. Lawrence Berkeley National Laboratroy and ICSI Center for Internet Research, 2004.
-
(2004)
The Bro 0.8 User Manual
-
-
Paxson, V.1
-
15
-
-
0032594954
-
Input space vs. feature space in kernel-based methods
-
September
-
B. Schölkopf, S. Mika, C.J.C. Burges, P. Knirsch, K.-R. Müller, G. Rätsch, and A.J. Smola. Input Space vs. Feature Space in Kernel-Based Methods. IEEE Transactions on Neural Networks, 10(5):1000-1017, September 1999.
-
(1999)
IEEE Transactions on Neural Networks
, vol.10
, Issue.5
, pp. 1000-1017
-
-
Schölkopf, B.1
Mika, S.2
Burges, C.J.C.3
Knirsch, P.4
Müller, K.-R.5
Rätsch, G.6
Smola, A.J.7
-
17
-
-
0347243182
-
Nonlinear component analysis as a kernel Eigenvalue problem
-
B. Schölkopf, A.J. Smola, and K.-R.Müller. Nonlinear component analysis as a kernel Eigenvalue problem. Neural Computation, 10:1299-1319, 1998.
-
(1998)
Neural Computation
, vol.10
, pp. 1299-1319
-
-
Schölkopf, B.1
Smola, A.J.2
Müller, K.-R.3
-
18
-
-
84898948710
-
Feature selection for SVMs
-
T.K. Leen, T.G. Dietterich, and V. Tresp, editors, MIT Press
-
J. Weston, S. Mukherjee, O. Chapelle, M. Pontil, T. Poggio, and V. Vapnik. Feature Selection for SVMs. In T.K. Leen, T.G. Dietterich, and V. Tresp, editors, Advances in Neural Information Processing Systems 13, pages 668-674. MIT Press, 2001.
-
(2001)
Advances in Neural Information Processing Systems
, vol.13
, pp. 668-674
-
-
Weston, J.1
Mukherjee, S.2
Chapelle, O.3
Pontil, M.4
Poggio, T.5
Vapnik, V.6
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