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portada Anomaly Detection System for Network Traffic using Data Mining
Type
Physical Book
Language
Inglés
Pages
144
Format
Paperback
Dimensions
22.9 x 15.2 x 0.9 cm
Weight
0.22 kg.
ISBN13
9786203305234

Anomaly Detection System for Network Traffic using Data Mining

Sandeep Chaurasia (Author) · Ruby Sharma (Author) · LAP Lambert Academic Publishing · Paperback

Anomaly Detection System for Network Traffic using Data Mining - Sharma, Ruby ; Chaurasia, Sandeep

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Synopsis "Anomaly Detection System for Network Traffic using Data Mining"

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.

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