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 …

DL‐IDS: Extracting Features Using CNN‐LSTM Hybrid Network for Intrusion Detection System

P Sun, P Liu, Q Li, C Liu, X Lu, R Hao… - Security and …, 2020 - Wiley Online Library
Many studies utilized machine learning schemes to improve network intrusion detection
systems recently. Most of the research is based on manually extracted features, but this …

lIDS-SIoEL: intrusion detection framework for IoT-based smart environments security using ensemble learning

C Hazman, A Guezzaz, S Benkirane, M Azrour - Cluster Computing, 2023 - Springer
Smart cities are being enabled all around the world by Internet of Things (IoT) applications.
A smart city idea necessitates the integration of information and communication …

An efficient federated learning system for network intrusion detection

J Li, X Tong, J Liu, L Cheng - IEEE Systems Journal, 2023 - ieeexplore.ieee.org
Network intrusion detection is used to detect unauthorized activities on a digital network,
with which the cybersecurity teams of organizations can then kick-start prevention protocols …

A review of federated learning in intrusion detection systems for iot

A Belenguer, J Navaridas, JA Pascual - arXiv preprint arXiv:2204.12443, 2022 - arxiv.org
Intrusion detection systems are evolving into intelligent systems that perform data analysis
searching for anomalies in their environment. The development of deep learning …

Intrusion detection for IoT based on improved genetic algorithm and deep belief network

Y Zhang, P Li, X Wang - IEEE Access, 2019 - ieeexplore.ieee.org
With the advent of the Internet of Things (IoT), the security of the network layer in the IoT is
getting more and more attention. The traditional intrusion detection technologies cannot be …

STG2P: A two-stage pipeline model for intrusion detection based on improved LightGBM and K-means

Z Zhang, L Wang, G Chen, Z Gu, Z Tian, X Du… - … Modelling Practice and …, 2022 - Elsevier
Network attack behavior is always mixed with a large number of normal communications,
which makes the attack characteristics only account for a very small fraction in the log data …

An intelligent and efficient network intrusion detection system using deep learning

M Imran, N Haider, M Shoaib, I Razzak - Computers and Electrical …, 2022 - Elsevier
With continuously escalating threats and attacks, accurate and timely intrusion detection in
communication networks is challenging. Many approaches have already been proposed …

Machine and deep learning solutions for intrusion detection and prevention in IoTs: A survey

PLS Jayalaxmi, R Saha, G Kumar, M Conti… - IEEE Access, 2022 - ieeexplore.ieee.org
The increasing number of connected devices in the era of Internet of Thing (IoT) has also
increased the number intrusions. Intrusion Detection System (IDS) is a secondary intelligent …

A two-stage intrusion detection system with auto-encoder and LSTMs

E Mushtaq, A Zameer, M Umer, AA Abbasi - Applied Soft Computing, 2022 - Elsevier
Abstract 'Curse of dimensionality'and the trade-off between low false alarm rate and high
detection rate are the major concerns while designing an efficient intrusion detection system …