Detection: Detecting Intrusions in Unlabeled Data Eleazar Eskin, Andrew...  Home/Search
Context
Related
| cmu.edu/~aarnold/./ids/uaddmsa02.ps Cached: PS.gz PS PDF This document uses CoBlitz to cache paper downloads. If your firewall is blocking outgoing connections to port 3125, you can use these links to download local copies.
Image Update HelpPS.gz PS PDF From: cmu.edu/~aarnold/research (more) (Enter author homepages) |
Rate this article:      (best)Comment on this article |
Abstract: Most current intrusion detection systems employ signature-based methods or data mining-based methods which rely on labeled training data. This training data is typically expensive to produce. We present a new geometric framework for unsupervised anomaly detection, which are algorithms that are designed to process unlabeled data. (Update)
Similar documents (at the sentence level):
7.8%: A Geometric Framework for Unsupervised Anomaly.. - Eskin, Arnold.. (2002) (Correct)
6.5%: Intrusion Detection with Unlabeled Data Using Clustering - Portnoy, Eskin, Stolfo (2001) (Correct)
Active bibliography (related documents): More All
0.8: Adaptive Model Generation: An Architecture for.. - Honig, Howard, Eskin, .. (2002) (Correct)
0.6: Modeling System Calls for Intrusion Detection with Dynamic.. - Eskin, Lee (2001) (Correct)
0.6: Adaptive Model Generation for Intrusion Detection Systems - Eskin, Miller, Zhong.. (2000) (Correct)
Similar documents based on text:
0.0: Unknown - (Correct)
BibTeX entry: (Update)
@misc{ intrusions-geometric,
author = "Detection Detecting Intrusions",
title = "A Geometric Framework for Unsupervised Anomaly",
url = "citeseer.ist.psu.edu/749707.html" }
Citations (may not include all citations):205 An Introduction to Support Vector Machines (context) - Cristianini, Shawe-Taylor - 2000
191 Fast training of support vector machines using sequential mi.. (context) - Platt - 1999
142 A sense of self for unix processes - Forrest, Hofmeyr et al. - 1996
133 Outliers in Statistical Data (context) - Barnett, Lewis - 1994
133 IEEE Transactions on Software Engineering (context) - Denning, detection - 1987
123 Bro: A system for detecting network intruders in real-time - Paxson - 1998
84 Data mining approaches for intrusion detection - Lee, Stolfo - 1998
70 The case against accuracy estimation for comparing induction.. - Provost, Fawcett et al. - 1998
62 The NIDES statistical component: description and justi - cat.. (context) - Javitz, Valdes - 1993
60 Algorithms for mining distance-based outliers in large datas.. - Knorr, Ng - 1998
60 Detecting intrusions using system calls: alternative data mo.. - Warrender, Forrest et al. - 1999
51 Convolution kernels on discrete structures - Haussler - 1999
42 Dynamic alignment kernels - Watkins - 2000
29 Estimating the support of a high-dimensional distribution - Sch, Platt et al. - 1999
27 A study in using neural networks for anomaly and misuse dete.. (context) - Ghosh, Schwartzbard - 1999
25 Sequence matching and learning in anomaly detection for comp.. - Lane, Brodley - 1997
24 LOF: identifying density-based local outliers - Breunig, Kriegel et al. - 2000
22 Anomaly detection over noisy data using learned probability .. - Eskin - 2000
15 Learning patterns from unix processes execution traces for i.. (context) - Lee, Stolfo et al. - 1997
14 A markov chain model of temporal behavior for anomaly detect.. - Ye - 2000
11 Intrusion detection with unlabeled data using clustering - Portnoy, Eskin et al. - 2001
11 Intrusion detect using sequences of system calls (context) - Hofmeyr, Forrest et al. - 1998
5 Ecient clustering of highdimensional data sets with applicat.. (context) - McCallum, Nigam et al. - 2000
5 Data mining in work ow environments: Experiences in intrusio.. (context) - Lee, Stolfo et al. - 1999
4 A statistically base system for prioritizing information exp.. (context) - Helman, Bhangoo - 1997
3 Modeling system calls for intrusion detection with dynamic w.. - Eskin, Lee et al. - 2001
3 Finding intentional knowledge of distance-based outliers (context) - Knorr, Ng - 1999
3 Ensemble-based adaptive intrusion detection (context) - Fan, Stolfo - 2002
Documents on the same site (http://www.cs.cmu.edu/~aarnold/research.html): More
Estimating the Support of a High-Dimensional Distribution - Bernhard Scholkopf John (1999) (Correct)
Time and Attention: Students, Sessions, and Tasks - Andrew Arnold Richard (Correct)
Reinforcement Learning in the Presence of Hidden States - Andrew Arnold Andrew (Correct)
Online articles have much greater impact More about CiteSeer.IST Add search form to your site Submit documents Feedback
CiteSeer.IST - Copyright Penn State and NEC