Network anomaly detection : a machine learning perspective /: a machine learning perspective. (2013)

• Record Type: Book
• Further Information: Note: Authors, Dhruba Kumar Bhattacharyya, Jugal Kumar Kalita.
• Authors: Bhattacharyya, Dhruba K
• Contents: Introduction; The Internet and Modern Networks; Network Vulnerabilities; Anomalies and Anomalies in Networks; Machine Learning; Prior Work on Network Anomaly Detection; Contributions of This Book; Organization; ; Networks and Anomalies ; Networking Basics; Anomalies in a Network; ; An Overview of Machine Learning Methods ; Introduction; Types of Machine Learning Methods; Supervised Learning: Some Popular Methods; Unsupervised Learning; Probabilistic Learning; Soft Computing; Reinforcement Learning; Hybrid Learning Methods; Discussion; ; Detecting Anomalies in Network Data ; Detection of Network Anomalies; Aspects of Network Anomaly Detection; Datasets; Discussion; ; Feature Selection ; Feature Selection vs. Feature Extraction; Feature Relevance; Advantages; Applications of Feature Selection; Prior Surveys on Feature Selection; Problem Formulation; Steps in Feature Selection; Feature Selection Methods: A Taxonomy; Existing Methods of Feature Selection; Subset Evaluation Measures; Systems and Tools for Feature Selection; Discussion; ; Approaches to Network Anomaly Detection ; Network Anomaly Detection Methods; Types of Network Anomaly Detection Methods; Anomaly Detection Using Supervised Learning; Anomaly Detection Using Unsupervised Learning; Anomaly Detection Using Probabilistic Learning; Anomaly Detection Using Soft Computing; Knowledge in Anomaly Detection; Anomaly Detection Using Combination Learners; Discussion; ; Evaluation Methods ; Accuracy; Performance; Completeness; Timeliness; Stability; Interoperability; Data Quality, Validity and Reliability; Alert Information; Unknown Attacks Detection; Updating References; Discussion; ; Tools and Systems ; Introduction; Attack Related Tools; Attack Detection Systems; Discussion; ; Open Issues, Challenges and Concluding Remarks ; Runtime Limitations for Anomaly Detection Systems; Reducing the False Alarm Rate; Issues in Dimensionality Reduction; Computational Needs of Network Defense Mechanisms; Designing Generic Anomaly Detection Systems; Handling Sophisticated Anomalies; Adaptability to Unknown Attacks; Detecting and Handling Large-Scale Attacks; Infrastructure Attacks; High Intensity Attacks; More Inventive Attacks; Concluding Remarks; ; References ; Index
• Publisher Details: Place of publication not identified : Chapman and Hall/CRC
• Publication Date: 2013
• Extent: 1 online resource (366 pages), (71 illustrations)
• Subjects: 005.8; Computer networks -- Security measures; Intrusion detection systems (Computer security); Machine learning
• Languages: English
• ISBNs: 9781466582095
• Related ISBNs: 146658209X
• Access Rights: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
• Access Usage: Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.