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Intrusion Detection based on Federated Learning: a systematic review
The evolution of cybersecurity is undoubtedly associated and intertwined with the
development and improvement of artificial intelligence (AI). As a key tool for realizing more …
development and improvement of artificial intelligence (AI). As a key tool for realizing more …
A data-driven network intrusion detection system using feature selection and deep learning
L Zhang, K Liu, X **e, W Bai, B Wu, P Dong - Journal of Information Security …, 2023 - Elsevier
Network intrusion detection system (NIDS) is an important line of defense for network
security as network attacks become more frequent. In this paper, we propose a data-driven …
security as network attacks become more frequent. In this paper, we propose a data-driven …
A soft actor-critic reinforcement learning algorithm for network intrusion detection
Network intrusion detection plays a very important role in network security. Although current
deep learning-based intrusion detection algorithms have achieved good detection …
deep learning-based intrusion detection algorithms have achieved good detection …
On the detection of lateral movement through supervised machine learning and an open-source tool to create turnkey datasets from sysmon logs
Lateral movement (LM) is a principal, increasingly common, tactic in the arsenal of
advanced persistent threat (APT) groups and other less or more powerful threat actors. It …
advanced persistent threat (APT) groups and other less or more powerful threat actors. It …
Best of both worlds: Detecting application layer attacks through 802.11 and non-802.11 features
Intrusion detection in wireless and, more specifically, Wi-Fi networks is lately increasingly
under the spotlight of the research community. However, the literature currently lacks a …
under the spotlight of the research community. However, the literature currently lacks a …
Wireless local area networks threat detection using 1D-CNN
M Natkaniec, M Bednarz - Sensors, 2023 - mdpi.com
Wireless Local Area Networks (WLANs) have revolutionized modern communication by
providing a user-friendly and cost-efficient solution for Internet access and network …
providing a user-friendly and cost-efficient solution for Internet access and network …
Towards Ensemble Feature Selection for Lightweight Intrusion Detection in Resource-Constrained IoT Devices.
The emergence of smart technologies and the wide adoption of the Internet of Things (IoT)
have revolutionized various sectors, yet they have also introduced significant security …
have revolutionized various sectors, yet they have also introduced significant security …
Meta‐analysis and systematic review for anomaly network intrusion detection systems: Detection methods, dataset, validation methodology, and challenges
Intrusion detection systems built on artificial intelligence (AI) are presented as latent
mechanisms for actively detecting fresh attacks over a complex network. The authors used a …
mechanisms for actively detecting fresh attacks over a complex network. The authors used a …
Rule-based system with machine learning support for detecting anomalies in 5g wlans
The purpose of this paper is to design and implement a complete system for monitoring and
detecting attacks and anomalies in 5G wireless local area networks. Regrettably, the …
detecting attacks and anomalies in 5G wireless local area networks. Regrettably, the …
Adversarial attack detection framework based on optimized weighted conditional stepwise adversarial network
Abstract Artificial Intelligence (AI)-based IDS systems are susceptible to adversarial attacks
and face challenges such as complex evaluation methods, elevated false positive rates …
and face challenges such as complex evaluation methods, elevated false positive rates …