Anomaly Detection System for Network Traffic using Data Mining
Machine Learning Perspective
(Sprache: Englisch)
Anomaly detection using Density Maximization Fuzzy C-means Algorithm: The rationale for the anomaly detection system using density maximization approach to the fuzzy c-means clustering algorithm. The workflow of a proposed anomaly detection system with...
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Anomaly detection using Density Maximization Fuzzy C-means Algorithm: The rationale for the anomaly detection system using density maximization approach to the fuzzy c-means clustering algorithm. The workflow of a proposed anomaly detection system with density maximization FCM algorithm. The framework of ensemble classifier-based anomaly detection - this approach of anomalous detection is based on the integration of multiple classifiers so that the weakness of one classifier can be compensated by the other classifier. The workflow of the proposed intrusion detection framework based on an ensemble classifier.
Autoren-Porträt von Ruby Sharma, Sandeep Chaurasia
Sharma, RubyDr. Ruby Sharma is working as an Associate Professor in the Institute of Information Technology & Management, Guru Gobind Singh Indraprastha University, New DelhiDr. Sandeep Chaurasia is working as a Professor in the Department of CSE, School of Computing & I.T. at Manipal University Jaipur.
Bibliographische Angaben
- Autoren: Ruby Sharma , Sandeep Chaurasia
- 2021, 144 Seiten, Maße: 22 cm, Kartoniert (TB), Englisch
- Verlag: LAP Lambert Academic Publishing
- ISBN-10: 6203305235
- ISBN-13: 9786203305234
Sprache:
Englisch
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