Investigating network intrusion detection datasets using machine learning

GC Amaizu, CI Nwakanma, JM Lee… - … on Information and …, 2020 - ieeexplore.ieee.org
There's been a series of datasets with regards to network intrusion detection in recent years,
and a significant number of studies has also been carried out using these datasets. In this …

Efficient deep CNN-BiLSTM model for network intrusion detection

J Sinha, M Manollas - Proceedings of the 2020 3rd International …, 2020 - dl.acm.org
The need for Network Intrusion Detection systems has risen since usage of cloud
technologies has become mainstream. With the ever growing network traffic, Network …

Network Intrusion Detection: A comparative study using state-of-the-art machine learning methods

M Rai, HL Mandoria - … conference on issues and challenges in …, 2019 - ieeexplore.ieee.org
Cyber threats are not only increasing with the years, but are also becoming harder to
recognize and evolving with time so that they can easily bypass normal antivirus. There …

Tl-nid: Deep neural network with transfer learning for network intrusion detection

M Masum, H Shahriar - 2020 15th International Conference for …, 2020 - ieeexplore.ieee.org
Network intrusion detection systems (NIDSs) play an essential role in the defense of
computer networks by identifying a computer networks' unauthorized access and …

[HTML][HTML] DCNNBiLSTM: An efficient hybrid deep learning-based intrusion detection system

V Hnamte, J Hussain - Telematics and Informatics Reports, 2023 - Elsevier
In recent years, all real-world processes have been shifted to the cyber environment
practically, and computers communicate with one another over the Internet. As a result, there …

Using deep learning techniques for network intrusion detection

S Al-Emadi, A Al-Mohannadi… - 2020 IEEE international …, 2020 - ieeexplore.ieee.org
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 …

Deep learning methods in network intrusion detection: A survey and an objective comparison

S Gamage, J Samarabandu - Journal of Network and Computer …, 2020 - Elsevier
The use of deep learning models for the network intrusion detection task has been an active
area of research in cybersecurity. Although several excellent surveys cover the growing …

A reliable network intrusion detection approach using decision tree with enhanced data quality

A Guezzaz, S Benkirane, M Azrour… - Security and …, 2021 - Wiley Online Library
Due to the recent advancements in the Internet of things (IoT) and cloud computing
technologies and growing number of devices connected to the Internet, the security and …

A one-dimensional convolutional neural network (1D-CNN) based deep learning system for network intrusion detection

EUH Qazi, A Almorjan, T Zia - Applied Sciences, 2022 - mdpi.com
The connectivity of devices through the internet plays a remarkable role in our daily lives.
Many network-based applications are utilized in different domains, eg, health care, smart …

Network intrusion detection system: a survey on artificial intelligence‐based techniques

MS Habeeb, TR Babu - Expert Systems, 2022 - Wiley Online Library
High data rate requirements in recent years have resulted in the massive expansion of
communication systems, network size and the amount of data generated and processed …