Bookcover of Intrusion Detection System Using Hybrid Gsa-kmeans
Booktitle:

Intrusion Detection System Using Hybrid Gsa-kmeans

LAP LAMBERT Academic Publishing (2014-11-24 )

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ISBN-13:

978-3-659-63033-0

ISBN-10:
3659630330
EAN:
9783659630330
Book language:
English
Blurb/Shorttext:
Security is an important aspect in our daily life. Intrusion Detection Systems (IDS) are developed to be the defense against security threats. Current signature based IDS like firewalls and antiviruses, which rely on labeled training data, generally cannot detect novel attacks. The purpose of this study is to improve the performance of IDS in terms of detection accuracy and reduce False Alarm Rate (FAR). Clustering is an important task in data mining that is used in IDS applications to detect novel attacks. Clustering refers to grouping together data objects so that objects within a cluster are similar to one another, while objects in different clusters are dissimilar. K-Means is a simple and efficient algorithm that is widely used for data clustering. However, its performance depends on the initial state of centroids and may trap in local optima. The Gravitational Search Algorithm (GSA) is one effective method for searching problem space to find a near optimal solution. In this study, a hybrid approach based on GSA and k-Means (GSA-kMeans), which uses the advantages of both algorithms, is presented.
Publishing house:
LAP LAMBERT Academic Publishing
Website:
https://www.lap-publishing.com/
By (author) :
Bibi Masoomeh Aslahi Shahri
Number of pages:
128
Published at:
2014-11-24
Stock:
Available
Category:
Informatics, IT
Price:
61.90 €
Keywords:
Data Mining, K-means, GSA, Machine Learning

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