Machine learning and deep learning methods for intrusion detection systems: A survey

H Liu, B Lang - applied sciences, 2019 - mdpi.com
Networks play important roles in modern life, and cyber security has become a vital research
area. An intrusion detection system (IDS) which is an important cyber security technique …

Deep learning for cyber security intrusion detection: Approaches, datasets, and comparative study

MA Ferrag, L Maglaras, S Moschoyiannis… - Journal of Information …, 2020 - Elsevier
In this paper, we present a survey of deep learning approaches for cyber security intrusion
detection, the datasets used, and a comparative study. Specifically, we provide a review of …

An effective feature engineering for DNN using hybrid PCA-GWO for intrusion detection in IoMT architecture

SP RM, PKR Maddikunta, M Parimala, S Koppu… - Computer …, 2020 - Elsevier
The entire computing paradigm is changed due to the technological advancements in
Information and Communication Technology (ICT). Due to these advancements, various …

Network threat detection using machine/deep learning in sdn-based platforms: a comprehensive analysis of state-of-the-art solutions, discussion, challenges, and …

N Ahmed, A Ngadi, JM Sharif, S Hussain, M Uddin… - Sensors, 2022 - mdpi.com
A revolution in network technology has been ushered in by software defined networking
(SDN), which makes it possible to control the network from a central location and provides …

Efficient cyber attack detection on the internet of medical things-smart environment based on deep recurrent neural network and machine learning algorithms

YK Saheed, MO Arowolo - IEEE Access, 2021 - ieeexplore.ieee.org
Information and communication technology (ICT) advancements have altered the entire
computing paradigm. As a result of these improvements, numerous new channels of …

DeepCoin: A novel deep learning and blockchain-based energy exchange framework for smart grids

MA Ferrag, L Maglaras - IEEE Transactions on Engineering …, 2019 - ieeexplore.ieee.org
In this paper, we propose a novel deep learning and blockchain-based energy framework
for smart grids, entitled DeepCoin. The DeepCoin framework uses two schemes, a …

Protocol-based deep intrusion detection for dos and ddos attacks using unsw-nb15 and bot-iot data-sets

M Zeeshan, Q Riaz, MA Bilal, MK Shahzad… - IEEE …, 2021 - ieeexplore.ieee.org
Since its inception, the Internet of Things (IoT) has witnessed mushroom growth as a
breakthrough technology. In a nutshell, IoT is the integration of devices and data such that …

Deep learning in IoT intrusion detection

S Tsimenidis, T Lagkas, K Rantos - Journal of network and systems …, 2022 - Springer
Abstract The Internet of Things (IoT) is the new paradigm of our times, where smart devices
and sensors from across the globe are interconnected in a global grid, and distributed …

GAN augmentation to deal with imbalance in imaging-based intrusion detection

G Andresini, A Appice, L De Rose, D Malerba - Future Generation …, 2021 - Elsevier
Nowadays attacks on computer networks continue to advance at a rate outpacing cyber
defenders' ability to write new attack signatures. This paper illustrates a deep learning …

Detection of real-time malicious intrusions and attacks in IoT empowered cybersecurity infrastructures

IA Kandhro, SM Alanazi, F Ali, A Kehar, K Fatima… - IEEE …, 2023 - ieeexplore.ieee.org
Computer viruses, malicious, and other hostile attacks can affect a computer network.
Intrusion detection is a key component of network security as an active defence technology …