TY - GEN
T1 - Using Deep Learning Techniques for Network Intrusion Detection
AU - Al-Emadi, Sara
AU - Al-Mohannadi, Aisha
AU - Al-Senaid, Felwa
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/2
Y1 - 2020/2
N2 - In recent years, there has been a significant increase in network intrusion attacks which raises a great concern from the privacy and security aspects. Due to the advancement of the technology, cyber-security attacks are becoming very complex such that the current detection systems are not sufficient enough to address this issue. Therefore, an implementation of an intelligent and effective network intrusion detection system would be crucial to solve this problem. In this paper, we use deep learning techniques, namely, Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN) to design an intelligent detection system which is able to detect different network intrusions. Additionally, we evaluate the performance of the proposed solution using different evaluation matrices and we present a comparison between the results of our proposed solution to find the best model for the network intrusion detection system.
AB - In recent years, there has been a significant increase in network intrusion attacks which raises a great concern from the privacy and security aspects. Due to the advancement of the technology, cyber-security attacks are becoming very complex such that the current detection systems are not sufficient enough to address this issue. Therefore, an implementation of an intelligent and effective network intrusion detection system would be crucial to solve this problem. In this paper, we use deep learning techniques, namely, Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN) to design an intelligent detection system which is able to detect different network intrusions. Additionally, we evaluate the performance of the proposed solution using different evaluation matrices and we present a comparison between the results of our proposed solution to find the best model for the network intrusion detection system.
KW - CNN
KW - Convolutional Neural Network
KW - Deep Learning
KW - Network Intrusion Detection
KW - Network Security
KW - Neural Network
KW - RNN
KW - Recurrent Neural Network
UR - http://www.scopus.com/inward/record.url?scp=85085516395&partnerID=8YFLogxK
U2 - 10.1109/ICIoT48696.2020.9089524
DO - 10.1109/ICIoT48696.2020.9089524
M3 - Conference contribution
AN - SCOPUS:85085516395
T3 - 2020 IEEE International Conference on Informatics, IoT, and Enabling Technologies, ICIoT 2020
SP - 171
EP - 176
BT - 2020 IEEE International Conference on Informatics, IoT, and Enabling Technologies, ICIoT 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 IEEE International Conference on Informatics, IoT, and Enabling Technologies, ICIoT 2020
Y2 - 2 February 2020 through 5 February 2020
ER -