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Network anomaly detection: a machine learning perspective
With the rapid rise in the ubiquity and sophistication of Internet technology and the accompanying growth in the number of network attacks, network intrusion detection has become increasingly important. Anomaly-based network intrusion detection refers to finding exceptional or nonconforming patterns...
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| Lenguaje: | eng |
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CRC Press
2013
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| Acceso en línea: | http://cds.cern.ch/record/1606318 |
| _version_ | 1780931677149724672 |
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| author | Bhattacharyya, Dhruba Kumar |
| author_facet | Bhattacharyya, Dhruba Kumar |
| author_sort | Bhattacharyya, Dhruba Kumar |
| collection | CERN |
| description | With the rapid rise in the ubiquity and sophistication of Internet technology and the accompanying growth in the number of network attacks, network intrusion detection has become increasingly important. Anomaly-based network intrusion detection refers to finding exceptional or nonconforming patterns in network traffic data compared to normal behavior. Finding these anomalies has extensive applications in areas such as cyber security, credit card and insurance fraud detection, and military surveillance for enemy activities. Network Anomaly Detection: A Machine Learning Perspective presents mach |
| id | cern-1606318 |
| institution | Organización Europea para la Investigación Nuclear |
| language | eng |
| publishDate | 2013 |
| publisher | CRC Press |
| record_format | invenio |
| spelling | cern-16063182020-07-16T20:00:59Zhttp://cds.cern.ch/record/1606318engBhattacharyya, Dhruba KumarNetwork anomaly detection: a machine learning perspectiveComputing and ComputersWith the rapid rise in the ubiquity and sophistication of Internet technology and the accompanying growth in the number of network attacks, network intrusion detection has become increasingly important. Anomaly-based network intrusion detection refers to finding exceptional or nonconforming patterns in network traffic data compared to normal behavior. Finding these anomalies has extensive applications in areas such as cyber security, credit card and insurance fraud detection, and military surveillance for enemy activities. Network Anomaly Detection: A Machine Learning Perspective presents machCRC Pressoai:cds.cern.ch:16063182013 |
| spellingShingle | Computing and Computers Bhattacharyya, Dhruba Kumar Network anomaly detection: a machine learning perspective |
| title | Network anomaly detection: a machine learning perspective |
| title_full | Network anomaly detection: a machine learning perspective |
| title_fullStr | Network anomaly detection: a machine learning perspective |
| title_full_unstemmed | Network anomaly detection: a machine learning perspective |
| title_short | Network anomaly detection: a machine learning perspective |
| title_sort | network anomaly detection: a machine learning perspective |
| topic | Computing and Computers |
| url | http://cds.cern.ch/record/1606318 |
| work_keys_str_mv | AT bhattacharyyadhrubakumar networkanomalydetectionamachinelearningperspective |