Deep ensemble-based efficient framework for network attack detection

F Rustam, A Raza, I Ashraf… - 2023 21st Mediterranean …, 2023 - ieeexplore.ieee.org
Nowadays, networks play a critical role in business, education, and daily life, allowing
people to communicate via different platforms across long distances. However, such …

LSTM-based network attack detection: performance comparison by hyper-parameter values tuning

MD Hossain, H Ochiai, D Fall… - 2020 7th IEEE …, 2020 - ieeexplore.ieee.org
Network attacks have been around since the beginning of the Internet and they are still
relevant due to the numerous attempts of independent hackers, cybercrime organizations …

Intrusion detection system using voting-based neural network

MH Haghighat, J Li - Tsinghua Science and Technology, 2021 - ieeexplore.ieee.org
Several security solutions have been proposed to detect network abnormal behavior.
However, successful attacks is still a big concern in computer society. Lots of security …

Intelligent techniques for detecting network attacks: review and research directions

M Aljabri, SS Aljameel, RMA Mohammad, SH Almotiri… - Sensors, 2021 - mdpi.com
The significant growth in the use of the Internet and the rapid development of network
technologies are associated with an increased risk of network attacks. Network attacks refer …

Ensemble-based machine learning techniques for attack detection

S Sharma, NS Yadav - 2021 9th International Conference on …, 2021 - ieeexplore.ieee.org
Internet and web services are fundamental use in our individual daily life. Individuals can
learn and work very well through the Internet. As Internet development increases, the …

A double-layer detection and classification approach for network attacks

C Sun, K Lv, C Hu, H Xie - 2018 27th International Conference …, 2018 - ieeexplore.ieee.org
Network intrusion detection system (NIDS) plays a crucial role in maintaining network
security. In this paper, we propose a novel double-layer detection and classification …

Novel class probability features for optimizing network attack detection with machine learning

A Raza, K Munir, MS Almutairi, R Sehar - IEEE Access, 2023 - ieeexplore.ieee.org
Network attacks refer to malicious activities exploiting computer network vulnerabilities to
compromise security, disrupt operations, or gain unauthorized access to sensitive …

Network intrusion detection system using voting ensemble machine learning

M Raihan-Al-Masud, HA Mustafa - 2019 IEEE International …, 2019 - ieeexplore.ieee.org
Due to increasing amount of cyber attack, there is a growing demand for Network intrusion
detection systems (NIDSs) which are necessary for defending from potential attacks …

A novel two-stage deep learning model for network intrusion detection: LSTM-AE

V Hnamte, H Nhung-Nguyen, J Hussain… - Ieee …, 2023 - ieeexplore.ieee.org
Machine learning and deep learning techniques are widely used to evaluate intrusion
detection systems (IDS) capable of rapidly and automatically recognizing and classifying …

Detection of network attacks using machine learning and deep learning models

KA Dhanya, S Vajipayajula, K Srinivasan… - Procedia Computer …, 2023 - Elsevier
Anomaly-based network intrusion detection systems are highly significant in detecting
network attacks. Robust machine learning and deep learning models for identifying network …