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โœฆ   LIBER   โœฆ

๐Ÿ“

Network anomaly detection: a machine learning perspective

โœ Scribed by Bhattacharyya, Dhruba K


Publisher
CRC Press, Taylor & Francis Group
Year
2014
Tongue
English
Leaves
364
Category
Library

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โœฆ Table of Contents


IntroductionThe Internet and Modern NetworksNetwork VulnerabilitiesAnomalies and Anomalies in NetworksMachine LearningPrior Work on Network Anomaly DetectionContributions of This BookOrganizationNetworks and AnomaliesNetworking BasicsAnomalies in a NetworkAn Overview of Machine Learning MethodsIntroductionTypes of Machine Learning MethodsSupervised Learning: Some Popular MethodsUnsupervised LearningProbabilistic LearningSoft ComputingReinforcement LearningHybrid Learning MethodsDiscussionDetecting Anomalies in Network DataDetection of Network AnomaliesAspects of Network Anomaly DetectionDatasetsDiscussionFeature SelectionFeature Selection vs. Feature ExtractionFeature RelevanceAdvantagesApplications of Feature SelectionPrior Surveys on Feature SelectionProblem FormulationSteps in Feature SelectionFeature Selection Methods: A TaxonomyExisting Methods of Feature SelectionSubset Evaluation MeasuresSystems and Tools for Feature SelectionDiscussionApproaches to Network Anomaly DetectionNetwork Anomaly Detection MethodsTypes of Network Anomaly Detection MethodsAnomaly Detection Using Supervised LearningAnomaly Detection Using Unsupervised LearningAnomaly Detection Using Probabilistic LearningAnomaly Detection Using Soft ComputingKnowledge in Anomaly DetectionAnomaly Detection Using Combination LearnersDiscussionEvaluation MethodsAccuracyPerformanceCompletenessTimelinessStabilityInteroperabilityData Quality, Validity and ReliabilityAlert InformationUnknown Attacks DetectionUpdating ReferencesDiscussionTools and SystemsIntroductionAttack Related ToolsAttack Detection SystemsDiscussionOpen Issues, Challenges and Concluding RemarksRuntime Limitations for Anomaly Detection SystemsReducing the False Alarm RateIssues in Dimensionality ReductionComputational Needs of Network Defense MechanismsDesigning Generic Anomaly Detection SystemsHandling Sophisticated AnomaliesAdaptability to Unknown AttacksDetecting and Handling Large-Scale AttacksInfrastructure AttacksHigh Intensity AttacksMore Inventive AttacksConcluding RemarksReferencesIndex

โœฆ Subjects


Aprendizaje automรกtico (Inteligencia artificial);Computer networks--Safety measures;Computer networks--Security measures;Intrusion detection systems (Computer security);Machine learning;Redes de ordenadores--Medidas de seguridad;Seguridad informรกtica;Redes de ordenadores -- Medidas de seguridad;Seguridad informaฬtica;Aprendizaje automaฬtico (Inteligencia artificial);Computer networks -- Security measures;Computer networks -- Safety measures


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