MARC record from Internet Archive

LEADER: 06575cam 22003734a 4500
001 9920948790001661
005 20161129142705.0
008 020325s2002 maua b 001 0 eng
010 $a 2002025668
015 $aGBA2-41580
020 $a1402070543 (alk. paper)
029 1 $aUKM$bbA241580
035 $a(CSdNU)u106943-01national_inst
035 $a(OCoLC)49421772
035 $a(Sirsi) 01-AAO-9913
040 $aDLC$cDLC$dC#P$dUKM$dOHX$dOrPss
042 $apcc
049 $aCNUM
050 00 $aQA76.9.D343$bA35 2002
072 7 $aQA$2lcco
245 00 $aApplications of data mining in computer security /$cedited by Daniel Barbara, Sushil Jajodia.
260 $aBoston :$bKluwer Academic Publishers,$cc2002.
300 $axx, 252 p. :$bill. ;$c25 cm.
440 0 $aAdvances in information security ;$v6
504 $aIncludes bibliographical references and index.
505 0 $aModern Intrusion Detection, Data Mining, and Degrees of Attack Guilt / Steven Noel, Duminda Wijesekera, Charles Youman -- Detection Strategies -- Misuse Detection -- Expert Systems -- Signature Analysis -- State-Transition Analysis -- Data Mining -- Other Approaches -- Anomaly Detection -- Statistical Methods -- Expert Systems -- Data Mining -- Other Approaches -- Data Sources -- Degrees of Attack Guilt -- Misuse Detection -- Knowledge-Based Methods -- Machine-Learning Methods -- Anomaly Detection -- Knowledge-Based Methods -- Statistical Methods -- Machine-Learning Methods -- Data Mining for Intrusion Detection / Klaus Julisch -- Data Mining Basics -- Data Mining, KDD, and Related Fields -- Some Data Mining Techniques -- Association Rules -- Frequent Episode Rules -- Classification -- Clustering -- Research Challenges in Data Mining -- Data Mining Meets Intrusion Detection -- MADAM ID -- ADAM -- Clustering of Unlabeled ID Data -- Mining the Alarm Stream -- Observations on the State of the Art -- Data Mining, but no Knowledge Discovery -- Disregard of Other KDD Steps -- Too Strong Assumptions -- Narrow Scope of Research Activities -- Future Research Directions -- An Architecture for Anomaly Detection / Daniel Barbara, Julia Couto, Sushil Jajodia, Ningning Wu -- Architecture -- Filter -- Profile -- Profile Builder -- Diagnoser -- ADAM: an implementation of the architecture -- Experiences -- Breaking the dependency on training data -- Future -- A Geometric Framework for Unsupervised Anomaly Detection / Eleazar Eskin, Andrew Arnold, Michael Prerau, Leonid Portnoy, Sal Stolfo -- Unsupervised Anomaly Detection -- A Geometric Framework for Unsupervised Anomaly Detection -- Feature Spaces -- Kernel Functions -- Convolution Kernels -- Detecting Outliers in Feature Spaces -- Algorithm 1: Cluster-based Estimation -- Algorithm 2: K-nearest neighbor -- Algorithm 3: One Class SVM -- Feature Spaces for Intrusion Detection -- Data-dependent Normalization Kernels -- Kernels for Sequences: The Spectrum Kernel -- Experiments -- Performance measures -- Data Set Descriptions -- Experimental Setup -- Experimental Results -- Fusing a Heterogeneous Alert Stream into Scenarios / Oliver Dain, Robert K. Cunningham -- Fusion Approach -- Architecture -- Probability Assignment -- Data Sources and Use -- Naive Technique -- Heuristic Technique -- Data Mining Techniques -- Experimental Results -- Naive Technique -- Heuristic Technique -- Data Mining Techniques -- System Benefits -- Discussion and Summary -- Using MIB II Variables for Network Intrusion Detection / Xinzhou Qin, Wenke Lee, Lundy Lewis, Joao B. D. Cabrera -- Background -- MIB II -- Entropy and Conditional Entropy -- Model Construction -- Model Architecture -- Anomaly Detection Module -- Anomaly Detection Model Design Overview -- Anomaly Detection Module Construction -- Experiments and Performance Evaluation -- Normal Data Sets -- Evaluation under Attacks -- Misuse Detection -- Anomaly Detection -- Related Work -- Conclusions and Future Work -- Adaptive Model Generation / Andrew Honig, Andrew Howard, Eleazar Eskin, Sal Stolfo -- Components of Adaptive Model Generation -- Real Time Components -- Data Warehouse -- Detection Model Management -- Data Analysis Engines -- Efficiency consideration -- Capabilities of Adaptive Model Generation -- Real Time Detection Capabilities -- Automatic Data Collection and Data Warehousing -- Model Generation and Management -- Data Analysis Capabilities -- Correlation of Multiple Sensors -- Model Generation Algorithms -- Misuse Detection -- Anomaly Detection -- Unsupervised Anomaly Detection -- Model Generation Example: SVM -- SVM Algorithm -- SVM for Misuse Detection in AMG -- Unsupervised SVM Algorithm -- Unsupervised SVM for Unsupervised Anomaly Detection -- System Example 1: Registry Anomaly Detection -- The RAD Data Model -- The RAD Sensor -- The RAD Classification Algorithm -- The RAD Detector -- System Example 2: HAUNT -- HAUNT Sensor -- HAUNT Classification Algorithm -- HAUNT Detector -- HAUNT Feature Extraction -- Proactive Intrusion Detection / Joao B. D. Cabrera, Lundy Lewis, Xinzhou Qin, Wenke Lee, Raman K. Mehra -- Information Assurance, Data Mining, and Proactive Intrusion Detection -- Intrusion Detection Systems -- A Thought Experiment -- Proactive Intrusion Detection -- A methodology for discovering precursors - Assumptions, Objectives, Procedure and Analysis -- Time Series, Multivariate Time Series and Collections -- Events, Event Sequences, Causal Rules and Precursor Rules -- Assumptions, Problem Set-Up, Objectives and Procedure -- Analysis - Detection and Gradation of Causality in Time Series -- The Granger Causality Test as an Exploratory Tool -- GCT and the Extraction of Precursor Rules - Modeling and Theoretical Developments -- A Case Study - Precursor Rules for Distributed Denial of Service Attacks -- DDoS Attacks and the experiments -- TFN2K Ping Flood - Extracting Precursor Rules -- E-mail Authorship Attribution for Computer Forensics / Olivier de Vel, Alison Anderson, Mal Corney, George Mohay -- Introduction and Motivation -- Computer Forensics -- E-mail Forensics -- Authorship Attribution -- E-mail Authorship Attribution -- Support Vector Machine Classifier -- E-mail Corpus and Methodology.
650 0 $aData mining.
650 0 $aComputer security.
700 1 $aBarbara, Daniel.
700 1 $aJajodia, Sushil.
938 $aOtto Harrassowitz$bHARR$nhar025022945$c132.00 DEM
948 $a10/11/2002$b10/23/2002
982 $aQA76.9.D343$aA35$a2002
999 $aQA 76.9 D343 A35 2002$wLC$c1$i31786101703160$d6/21/2011$e8/21/2004 $f6/15/2004$g1$lCIRCSTACKS$mNULS$n4$q2$rY$sY$tBOOK$u10/23/2002