… the right data features is crucial, maximising the detection accuracy and computational …
analyses feature sets’ importance and predictive power for detecting network attacks. Three …

… time to detect attacks. This paper proposes a feature selection for intrusion detection systems
(… top 50% features for the detection of DoS and DDoS attacks. The proposed system obtains …

… in IoT networks have demonstrated the unreliability of current Network Intrusion Detection
… In an analysis of related works, it was observed that most researchers aim to obtain better …

… of P ≪ M features, ie, Χ FS ∈ ℝ N×P , where p are relevant features of the target class. In
this research, we endeavored to find an optimal method to detect security violations in the IoT …

… This work proposes a deep learning GRU-based framework for intrusion detection in the
SDN-enabled IoT environment. The framework extracts internal feature representations from …

… to various intrusion attacks. We devised a model named DF-IDS for detecting intrusions in
IoT … datasets because it is the data that mainly limit the intrusion detection systems research. …

… In summary, the main proposal and contribution of this paper is to provide a network
intrusion detection system for IoT devices that has three main characteristics: …

… security in the IoT. Herein, we propose a solution for an intelligent intrusion detection system,
which … neural network (SSO-BNMCNN)-based multivariate feature analysis for IoT (Fig. 1). …

… In recent years, IoT intrusion detection has drawn attention from a research perspective. As
… to detect them evolve, an increasing number of research topics come to light. Therefore, it is …

… widely used DL models for intrusion detection. The authors conducted … significant IoT network
features for intrusion detection. The … [24] for malicious activity detection in IoT networks. The …