Variance-Index Based Feature Selection Algorithm for Network Intrusion Detection
نویسندگان
چکیده
منابع مشابه
A Parallel Genetic Algorithm Based Method for Feature Subset Selection in Intrusion Detection Systems
Intrusion detection systems are designed to provide security in computer networks, so that if the attacker crosses other security devices, they can detect and prevent the attack process. One of the most essential challenges in designing these systems is the so called curse of dimensionality. Therefore, in order to obtain satisfactory performance in these systems we have to take advantage of app...
متن کاملA Parallel Genetic Algorithm Based Method for Feature Subset Selection in Intrusion Detection Systems
Intrusion detection systems are designed to provide security in computer networks, so that if the attacker crosses other security devices, they can detect and prevent the attack process. One of the most essential challenges in designing these systems is the so called curse of dimensionality. Therefore, in order to obtain satisfactory performance in these systems we have to take advantage of app...
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Nowadays, data mining has been playing an important role in the various disciplines of sciences and technologies. For computer security, data mining are introduced for helping intrusion detection System (IDS) to detect intruders correctly. However, one of the essential procedures of data mining is feature selection, which is the technique (commonly used in machine learning) for selecting a subs...
متن کاملLinear Correlation-Based Feature Selection For Network Intrusion Detection Model
Feature selection is a preprocessing phase to machine learning, which leads to increase the classification accuracy and reduce its complexity. However, the increase of data dimensionality poses a challenge to many existing feature selection methods. This paper formulates and validates a method for selecting optimal feature subset based on the analysis of the Pearson correlation coefficients. We...
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We show the use of a genetic algorithm for feature subset selection over feature vectors that describe the system calls executed by privileged processes. Genetic feature subset selection significantly reduces the number of features used without adversely affecting the accuracy of the predictions.
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ژورنال
عنوان ژورنال: IOSR Journal of Computer Engineering
سال: 2016
ISSN: 2278-8727,2278-0661
DOI: 10.9790/0661-1804050111