A New Feature Selection Approach and Classification Technique for Current Intrusion Detection System
[ X ]
Tarih
2021
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Institute of Electrical and Electronics Engineers Inc.
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
These days, various devices including computers, smartphones, internet of things (IoT), and cloud services are using computer networks for data communications. As the computer network is being used extensively, it becomes the target of many attacks. It can be different attacks such as denial of service attack (DoS), remote to user attack (R2L), user to remote attack (U2R), and probing attack. To protect communication networks from network-based attacks, intrusion detection systems (IDSs) have been proposed in many studies. However, today IDSs are not good enough to detect new attack types in the communication networks. To increase the efficiency of the current IDSs, a subset of features needs to be obtained before performing the machine learning classifiers. In this study, a new feature selection method is proposed for current IDSs. In addition, the proposed method is combined with machine learning classifiers and tested on KDD '99 dataset and %99.81 accuracy rate was obtained. The obtained performance is pretty high to separate network attacks from the normal traffic. © 2021 IEEE
Açıklama
6th International Conference on Computer Science and Engineering, UBMK 2021 -- 15 September 2021 through 17 September 2021 -- Ankara -- 176826
Anahtar Kelimeler
Attacks detection, Feature engineering, Feature selection, Intrusion detection
Kaynak
Proceedings - 6th International Conference on Computer Science and Engineering, UBMK 2021
WoS Q Değeri
Scopus Q Değeri
N/A
