-
1
-
-
4544229404
-
ADAM: Detecting intrusions by data mining
-
West Point, NY, June
-
D. Barbara, J. Couto, S. Jajodia, L. Popyack, and N. Wu. ADAM: Detecting intrusions by data mining. In Proc. of the IEEE Workshop on IAS, pages 11-16, West Point, NY, June 2001.
-
(2001)
Proc. of the IEEE Workshop on IAS
, pp. 11-16
-
-
Barbara, D.1
Couto, J.2
Jajodia, S.3
Popyack, L.4
Wu, N.5
-
2
-
-
32844462055
-
Detecting novel network intrusions using bayes estimators
-
Chicago, IL, April
-
D. Barbara, N. Wu, and S. Jajodia. Detecting novel network intrusions using bayes estimators. In First SIAM Conference on Data Mining, Chicago, IL, April 2001.
-
(2001)
First SIAM Conference on Data Mining
-
-
Barbara, D.1
Wu, N.2
Jajodia, S.3
-
3
-
-
77952380096
-
Mining distance-based outliers in near linear time with randomization and a simple pruning rule
-
New York, USA
-
S. Bay and M. Schwabacher. Mining distance-based outliers in near linear time with randomization and a simple pruning rule. In Proc. of the ninth ACM SIGKDD, pages 29-38, New York, USA, 2003.
-
(2003)
Proc. of the Ninth ACM SIGKDD
, pp. 29-38
-
-
Bay, S.1
Schwabacher, M.2
-
4
-
-
79952952185
-
Critical study of supervised learning techniques in predicting attacks
-
R. Beghdad. Critical study of supervised learning techniques in predicting attacks. Information Security Journal: A Global Perspective, 19(1):22-35, 2010.
-
(2010)
Information Security Journal: A Global Perspective
, vol.19
, Issue.1
, pp. 22-35
-
-
Beghdad, R.1
-
6
-
-
79953835698
-
RODD: An effective outlier detection technique for large datasets
-
N. M. et. al. editor, volume 133 of CCIS, Springer
-
M. H. Bhuyan, D. K. Bhattacharyya, and J. K. Kalita. RODD: An effective outlier detection technique for large datasets. In N. M. et. al., editor, Proc. of CCSIT'11, volume 133 of CCIS, Part-III, pages 76-84. Springer, 2010.
-
(2010)
Proc. of CCSIT'11
, Issue.PART-III
, pp. 76-84
-
-
Bhuyan, M.H.1
Bhattacharyya, D.K.2
Kalita, J.K.3
-
7
-
-
0039253819
-
LOF: Identifying density-based local outliers
-
Dallas, Texas, USA
-
M. M. Breunig, H.-P. Kriegel, R. T. Ng, and J. Sander. LOF: Identifying density-based local outliers. In ACM SIGMOD on Management of Data, pages 386-395, Dallas, Texas, USA, 2000.
-
(2000)
ACM SIGMOD on Management of Data
, pp. 386-395
-
-
Breunig, M.M.1
Kriegel, H.-P.2
Ng, R.T.3
Sander, J.4
-
8
-
-
33745441630
-
-
chapter The MINDS-Minnesota Intrusion Detection System, MIT Press
-
L. Ertoz, E. Eilertson, A. Lazarevic, P. Tan, J. Srivastava, V. Kumar, and P. Dokas. Next Generation Data Mining, chapter The MINDS-Minnesota Intrusion Detection System. MIT Press, 2004.
-
(2004)
Next Generation Data Mining
-
-
Ertoz, L.1
Eilertson, E.2
Lazarevic, A.3
Tan, P.4
Srivastava, J.5
Kumar, V.6
Dokas, P.7
-
9
-
-
0038324535
-
Applications of data mining in computer security
-
Kluwer
-
E. Eskin, A. Arnold, M. Prerau, L. Portnoy, and S. Stolfo. Applications of Data Mining in Computer Security, A geometric framework for unsupervised anomaly detection : Detecting intrusions in unlabeled data. Kluwer, 2002.
-
(2002)
A Geometric Framework for Unsupervised Anomaly Detection : Detecting Intrusions in Unlabeled Data
-
-
Eskin, E.1
Arnold, A.2
Prerau, M.3
Portnoy, L.4
Stolfo, S.5
-
10
-
-
78649934709
-
-
Irvine, CA: University of California, School of Information and Computer Sciences
-
A. Frank and A. Asuncion. UCI Machine Learning Repository [http://archive.ics.uci.edu/ml], 2010. Irvine, CA: University of California, School of Information and Computer Sciences.
-
(2010)
UCI Machine Learning Repository
-
-
Frank, A.1
Asuncion, A.2
-
11
-
-
79952963997
-
-
KDDCUP99. October 28
-
KDDCUP99. Winning strategy in kdd99. http://kdd.ics.uci.edu/databases/ kddcup99/kddcup99.html October 28 1999.
-
(1999)
Winning Strategy in Kdd99
-
-
-
13
-
-
85084163349
-
Data mining approaches for intrusion detection
-
USENIX Association, Berkeley, CA, USA
-
W. Lee and S. J. Stolfo. Data mining approaches for intrusion detection. In Proc. of the 7th conference on USENIX Security Symposium - Volume 7, pages 6-6, USENIX Association, Berkeley, CA, USA, 1998.
-
(1998)
Proc. of the 7th Conference on USENIX Security Symposium
, vol.7
, pp. 6
-
-
Lee, W.1
Stolfo, S.J.2
-
14
-
-
84878080825
-
An efficient reference-based approach to outlier detection in large datasets
-
Washington, DC, USA, IEEE
-
Y. Pei, O. R. Zaiane, and Y. Gao. An efficient reference-based approach to outlier detection in large datasets. In Proc. of the Sixth International Conference on Data Mining, pages 478-487, Washington, DC, USA, 2006. IEEE.
-
(2006)
Proc. of the Sixth International Conference on Data Mining
, pp. 478-487
-
-
Pei, Y.1
Zaiane, O.R.2
Gao, Y.3
-
15
-
-
34548752457
-
Incremental local outlier detection for data streams
-
DOI 10.1109/CIDM.2007.368917, 4221341, Proceedings of the 2007 IEEE Symposium on Computational Intelligence and Data Mining, CIDM 2007
-
D. Pokrajac, A. Lazarevic, and L. J. Latecki. Incremental local outlier detection for data streams. In IEEE Symposium on Computational Intelligence and Data Mining, pages 504-515, Honolulu, HI, April 2007. IEEE. (Pubitemid 47431481)
-
(2007)
Proceedings of the 2007 IEEE Symposium on Computational Intelligence and Data Mining, CIDM 2007
, pp. 504-515
-
-
Pokrajac, D.1
Lazarevic, A.2
Latecki, L.J.3
-
16
-
-
0038663185
-
Intrusion detection with unlabeled data using clustering
-
Philadelphia, PA
-
L. Portnoy, E. Eskin, and S. Stolfo. Intrusion detection with unlabeled data using clustering. In Proc. of ACM CSS Workshop on DMAS, pages 5-8, Philadelphia, PA, 2001.
-
(2001)
Proc. of ACM CSS Workshop on DMAS
, pp. 5-8
-
-
Portnoy, L.1
Eskin, E.2
Stolfo, S.3
-
17
-
-
51349120553
-
A novel outlier detection scheme for network intrusion detection systems
-
Washington, DC, USA, IEEE CS
-
K. Prakobphol and J. Zhan. A novel outlier detection scheme for network intrusion detection systems. In Proc. of the 2008 International Conference on ISA, pages 555-560, Washington, DC, USA, 2008. IEEE CS.
-
(2008)
Proc. of the 2008 International Conference on ISA
, pp. 555-560
-
-
Prakobphol, K.1
Zhan, J.2
-
18
-
-
35248842651
-
Detecting anomalous network traffic with self-organizing maps
-
LNCS, Springer
-
M. Ramadas, S. Ostermann, and B. Tjaden. Detecting anomalous network traffic with self-organizing maps. In Recent Advances in Intrusion Detection, LNCS, pages 36-54. Springer, 2003.
-
(2003)
Recent Advances in Intrusion Detection
, pp. 36-54
-
-
Ramadas, M.1
Ostermann, S.2
Tjaden, B.3
-
19
-
-
27144518261
-
A novel anomaly detection scheme based on principal component classifier
-
USA
-
M. L. Shyu, S. C. Chen, K. Sarinnapakorn, and L. Chang. A novel anomaly detection scheme based on principal component classifier. In Proc. of the IEEE Foundations and New Directions of Data Mining Workshop, pages 172-179, USA, 2003.
-
(2003)
Proc. of the IEEE Foundations and New Directions of Data Mining Workshop
, pp. 172-179
-
-
Shyu, M.L.1
Chen, S.C.2
Sarinnapakorn, K.3
Chang, L.4
-
20
-
-
49649123060
-
A novel covariance matrix based approach for detecting network anomalies
-
Washington, DC, USA
-
M. Tavallaee, W. Lu, S. A. Iqbal, and A. A. Ghorbani. A novel covariance matrix based approach for detecting network anomalies. In Proc. of the Communication Networks and Services Research Conference, pages 75-81, Washington, DC, USA, 2008.
-
(2008)
Proc. of the Communication Networks and Services Research Conference
, pp. 75-81
-
-
Tavallaee, M.1
Lu, W.2
Iqbal, S.A.3
Ghorbani, A.A.4
-
22
-
-
33746076451
-
One-class support vector machine for anomaly network traffic detection
-
Cairns, Australia
-
Q. A. Tran, H. Duan, and X. Li. One-class support vector machine for anomaly network traffic detection. In The 2nd Network Research Workshop of the 18th APAN, Cairns, Australia, 2004.
-
(2004)
2nd Network Research Workshop of the 18th APAN
-
-
Tran, Q.A.1
Duan, H.2
Li, X.3
-
23
-
-
42549142161
-
Anomaly based network intrusion detection with unsupervised outlier detection
-
DOI 10.1109/ICC.2006.255127, 4024522, 2006 IEEE International Conference on Communications, ICC 2006
-
J. Zhang and M. Zulkernine. Anomaly based network intrusion detection with unsupervised outlier detection. In IEEE International Conference on Communications, volume 5, pages 2388-2393, june 2006. (Pubitemid 351575588)
-
(2006)
IEEE International Conference on Communications
, vol.5
, pp. 2388-2393
-
-
Zhang, J.1
Zulkernine, M.2
|