-
1
-
-
0001793263
-
Self-Nonself Discrimination in a Computer
-
Forrest, S., Perelson, A., Allen, L., Cherukury, R.: Self-Nonself Discrimination in a Computer. In Proc. IEEE Synip. on research in security and privacy (1994)
-
(1994)
Proc. IEEE Synip. on research in security and privacy
-
-
Forrest, S.1
Perelson, A.2
Allen, L.3
Cherukury, R.4
-
2
-
-
1442339891
-
Anomaly Detection using Negative Selection based on the Rcontiguous Matching Rule
-
ICARIS
-
Singh, S.: Anomaly Detection using Negative Selection based on the Rcontiguous Matching Rule. In 1st International Conference on Artificial Immune Systems (ICARIS) (2002) 99-106
-
(2002)
1st International Conference on Artificial Immune Systems
, pp. 99-106
-
-
Singh, S.1
-
4
-
-
0001858279
-
Sequence Matching and Learning in Anomaly Detection for Computer Security
-
Fawcett, Haimowitz, Provost, Stolfo, eds, AAAI Press
-
Lane, T., Brodley, CE.: Sequence Matching and Learning in Anomaly Detection for Computer Security. In AI Approaches to Fraud Detection and Risk Management (Fawcett, Haimowitz, Provost, Stolfo, eds.), AAAI Press (1997) 43-49
-
(1997)
AI Approaches to Fraud Detection and Risk Management
, pp. 43-49
-
-
Lane, T.1
Brodley, C.E.2
-
6
-
-
0142095474
-
Using Artificial Anomalies to Detect Unknown and Known Network Intrusions
-
Fan, W., Lee, W., Miller, M., Stolfo, S., Chan, P.: Using Artificial Anomalies to Detect Unknown and Known Network Intrusions. In Proc. 1st IEEE International conference on Data Mining (2001)
-
(2001)
Proc. 1st IEEE International conference on Data Mining
-
-
Fan, W.1
Lee, W.2
Miller, M.3
Stolfo, S.4
Chan, P.5
-
8
-
-
0038663185
-
Intrusion Detection with Unlabeled Data using Clustering
-
Philadelphia, PA
-
Portnoy, L., Eskin, E., Stolfo, S.J.: Intrusion Detection with Unlabeled Data using Clustering. In Proc. ACM CSS Workshop on Data Mining Applied to Security (DMSA2001), Philadelphia, PA (2001)
-
(2001)
Proc. ACM CSS Workshop on Data Mining Applied to Security (DMSA2001)
-
-
Portnoy, L.1
Eskin, E.2
Stolfo, S.J.3
-
10
-
-
0006928503
-
A Structure Adapting Feature Map for Optimal Cluster Representation
-
Neural Information Processing
-
Alahakoon, L.D., Halgamuge, S.K., Srinivasan, B.: A Structure Adapting Feature Map for Optimal Cluster Representation. In Proc. Int. Conf. Neural Information Processing (1998) 809-812
-
(1998)
Proc. Int. Conf
, pp. 809-812
-
-
Alahakoon, L.D.1
Halgamuge, S.K.2
Srinivasan, B.3
-
14
-
-
28444457043
-
An Unsupervised Anomaly Intrusion Detection Algorithm based on Swarm Intelligence
-
Guangzhou
-
Feng, Y., Wu, Z.F., Wu, K.G.: An Unsupervised Anomaly Intrusion Detection Algorithm based on Swarm Intelligence. 2005 International Conference on Machine Learning and Cybernetics, ICMLC 2005, Guangzhou (2005)
-
(2005)
2005 International Conference on Machine Learning and Cybernetics, ICMLC
-
-
Feng, Y.1
Wu, Z.F.2
Wu, K.G.3
-
15
-
-
24944561411
-
Intrusion Detection based on Dynamic SelfOrganizing Map Neural Network Clustering
-
Feng, Y., Wu, K.G., Wu, Z.F.: Intrusion Detection based on Dynamic SelfOrganizing Map Neural Network Clustering. Lecture Notes in Computer Science (2005)
-
(2005)
Lecture Notes in Computer Science
-
-
Feng, Y.1
Wu, K.G.2
Wu, Z.F.3
-
17
-
-
0344439823
-
-
Published in Data Mining for Security Applications, Kluwer
-
Eskin, E., Arnold, A., Prerau, M.: A Geometric Framework for Unsupervised Anomaly Detection: Detecting Intrusions in Unlabeled Data. Published in Data Mining for Security Applications, Kluwer (2002)
-
(2002)
A Geometric Framework for Unsupervised Anomaly Detection: Detecting Intrusions in Unlabeled Data
-
-
Eskin, E.1
Arnold, A.2
Prerau, M.3
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