Anomaly Detection System for Network Traffic using Data Mining

Anomaly Detection System for Network Traffic using Data Mining

EnglishPaperback / softback
Sharma, Ruby
LAP Lambert Academic Publishing
EAN: 9786203305234
On order
Delivery on Monday, 27. of July 2026
CZK 1,607
Common price CZK 1,785
Discount 10%
pc
Do you want this product today?
Megabooks Praha Korunní
not available
Librairie Francophone Praha Štěpánská
not available
Megabooks Ostrava
not available
Megabooks Olomouc
not available
Megabooks Plzeň
not available
Megabooks Brno
not available
Megabooks Hradec Králové
not available
Megabooks České Budějovice
not available
Megabooks Liberec
not available

Detailed information

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.
EAN 9786203305234
ISBN 6203305235
Binding Paperback / softback
Publisher LAP Lambert Academic Publishing
Publication date January 19, 2021
Pages 144
Language English
Dimensions 229 x 152 x 9
Readership General
Authors Chaurasia, Sandeep; Sharma, Ruby
Manufacturer information
The manufacturer's contact information is currently not available online, we are working intensively on the axle. If you need information, write us on [email protected], we will be happy to provide it.