Network intrusion detection system: A systematic study of machine learning and deep learning approaches
The rapid advances in the internet and communication fields have resulted in a huge
increase in the network size and the corresponding data. As a result, many novel attacks are …
increase in the network size and the corresponding data. As a result, many novel attacks are …
Comparative analysis of intrusion detection systems and machine learning based model analysis through decision tree
Cyber-attacks pose increasing challenges in precisely detecting intrusions, risking data
confidentiality, integrity, and availability. This review paper presents recent IDS taxonomy, a …
confidentiality, integrity, and availability. This review paper presents recent IDS taxonomy, a …
Application of deep reinforcement learning to intrusion detection for supervised problems
The application of new techniques to increase the performance of intrusion detection
systems is crucial in modern data networks with a growing threat of cyber-attacks. These …
systems is crucial in modern data networks with a growing threat of cyber-attacks. These …
Transport and application layer DDoS attacks detection to IoT devices by using machine learning and deep learning models
From smart homes to industrial environments, the IoT is an ally to easing daily activities,
where some of them are critical. More and more devices are connected to and through the …
where some of them are critical. More and more devices are connected to and through the …
Anomaly-based intrusion detection system for IoT application
Abstract Internet-of-Things (IoT) connects various physical objects through the Internet and it
has a wide application, such as in transportation, military, healthcare, agriculture, and many …
has a wide application, such as in transportation, military, healthcare, agriculture, and many …
[HTML][HTML] Intrusion detection system in distributed cloud computing: Hybrid clustering and classification methods
Cloud Computing is popular nowadays due to its storage and data access services. Security
and privacy are prime concerns when network threats increase. Cloud computing offers …
and privacy are prime concerns when network threats increase. Cloud computing offers …
Deep SARSA-based reinforcement learning approach for anomaly network intrusion detection system
S Mohamed, R Ejbali - International Journal of Information Security, 2023 - Springer
The growing evolution of cyber-attacks imposes a risk in network services. The search of
new techniques is essential to detect and classify dangerous attacks. In that regard, deep …
new techniques is essential to detect and classify dangerous attacks. In that regard, deep …
Evaluation of cybersecurity data set characteristics for their applicability to neural networks algorithms detecting cybersecurity anomalies
Artificial intelligence algorithms have a leading role in the field of cybersecurity and attack
detection, being able to present better results in some scenarios than classic intrusion …
detection, being able to present better results in some scenarios than classic intrusion …
A multi-task based deep learning approach for intrusion detection
Q Liu, D Wang, Y Jia, S Luo, C Wang - Knowledge-Based Systems, 2022 - Elsevier
With the frequent occurrence of cyber-security incidents, intrusion detection system (IDS)
has been payed more and more attention recently. However, detecting attacks from traffic …
has been payed more and more attention recently. However, detecting attacks from traffic …
Hierarchical federated learning for collaborative IDS in IoT applications
As the Internet-of-Things devices are being very widely adopted in all fields, such as smart
houses, healthcare, and transportation, extremely huge amounts of data are being gathered …
houses, healthcare, and transportation, extremely huge amounts of data are being gathered …