Categories Malware using Neural Networks based on Feature Selection by Genetic algorithm
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| Format: | Artículo científico |
| Language: | en |
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Universidade Federal de Santa Maria
2015
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| _version_ | 1876473545239822336 |
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| author | Fatemeh Farahmand |
| author_facet | Fatemeh Farahmand |
| contents | Categories Malware using Neural Networks based on Feature Selection by Genetic algorithm Fatemeh Farahmand Seyed Javad Mirabed Estudios Ambientales IDS Neural networks genetic algorithm feature selection Concurrent with the ever-increasing growth of information and communication technology (ICT) and the dramatic expansion of computer networks, we observe different forms of attacks and intrusions to networks; thus intrusion detection systems (IDSs) are considered as a vital part of each network connected to internet in the modern world. Neural networks are considered as a popular method used in IDS. Two major problems in these networks, i.e. long training time and inattention to features' domain, have made necessary development and/or improvement of the model. Feature selection techniques are used in the neural networks in order to develop a new model to speed up the attack detection, to reduce error notification rate and finally to enhance system's efficiency. In this study, for enhancing efficiency of the neural network in detecting intrusions, a genetic algorithm was used for selecting features. The suggested model was examined and assessed on NSL-KDD dataset which is the modified version of the KDD-CUP99. The experimental results indicate that the suggested model is very efficient in enhancing precision and recall of attack detection and reducing the error notification rate and also is able to offer more accurate detections in contrast to the basic models. 2015 artículo científico 0100-8307 https://www.redalyc.org/articulo.oa?id=467547683022 en http://www.redalyc.org/revista.oa?id=4675 Ciência e Natura application/pdf Universidade Federal de Santa Maria Ciência e Natura (Brasil) Num.6-2 Vol.37 |
| format | Artículo científico |
| id | redalyc_467547683022 |
| institution | Redalyc |
| language | en |
| publishDate | 2015 |
| publisher | Universidade Federal de Santa Maria |
| spellingShingle | Categories Malware using Neural Networks based on Feature Selection by Genetic algorithm Fatemeh Farahmand Estudios Ambientales IDS Neural networks genetic algorithm feature selection Categories Malware using Neural Networks based on Feature Selection by Genetic algorithm Fatemeh Farahmand Seyed Javad Mirabed Estudios Ambientales IDS Neural networks genetic algorithm feature selection Concurrent with the ever-increasing growth of information and communication technology (ICT) and the dramatic expansion of computer networks, we observe different forms of attacks and intrusions to networks; thus intrusion detection systems (IDSs) are considered as a vital part of each network connected to internet in the modern world. Neural networks are considered as a popular method used in IDS. Two major problems in these networks, i.e. long training time and inattention to features' domain, have made necessary development and/or improvement of the model. Feature selection techniques are used in the neural networks in order to develop a new model to speed up the attack detection, to reduce error notification rate and finally to enhance system's efficiency. In this study, for enhancing efficiency of the neural network in detecting intrusions, a genetic algorithm was used for selecting features. The suggested model was examined and assessed on NSL-KDD dataset which is the modified version of the KDD-CUP99. The experimental results indicate that the suggested model is very efficient in enhancing precision and recall of attack detection and reducing the error notification rate and also is able to offer more accurate detections in contrast to the basic models. 2015 artículo científico 0100-8307 https://www.redalyc.org/articulo.oa?id=467547683022 en http://www.redalyc.org/revista.oa?id=4675 Ciência e Natura application/pdf Universidade Federal de Santa Maria Ciência e Natura (Brasil) Num.6-2 Vol.37 |
| title | Categories Malware using Neural Networks based on Feature Selection by Genetic algorithm |
| topic | Estudios Ambientales IDS Neural networks genetic algorithm feature selection |
| url | https://www.redalyc.org/articulo.oa?id=467547683022 |