22 hours ago · This paper proposes a machine learning-based intrusion detection system (ML-IDS) for detecting IoT network attacks. The primary objective of this research ...

7 days ago · This paper introduces a novel intrusion detection technique that diverges from traditional methods by leveraging Recurrent Neural Networks (RNNs) for both data ...

2 days ago · Anomaly-based intrusion detection systems analyze and classify system and network behavior as normal or abnormal to detect cyberattacks. These systems aim for ...

7 days ago · An intrusion detection system (IDS) which is an important cyber security technique, monitors the state of software and hardware running in the network. Despite ...

4 days ago · A deep learning ensemble for network anomaly and cyber-attack detection ... attacks detection to IoT devices by using machine learning and deep learning models.

7 days ago · The research paper presents a novel IoT-IDS model titled “CVS-FLN” for detecting intrusions in the IoT network based on metaheuristic and neural network ...

5 days ago · With an emphasis on a sophisticated intrusion detection and prevention system based on Deep Belief Symmetrical Networks (DBNs), this study investigates cutting ...

4 days ago · Mostly, AI-based methods for detecting anomalies include deep learning and Support Vector Machine (SVM). A hybrid technique often becomes effective in ...

1 day ago · The current approach to network intrusion detection using Convolutional Neural Networks (CNNs) leverages various machine learning and deep learning techniques.

2 days ago · The security challenges at various IoT layers are unveiled in this review paper along with the existing mitigation strategies such as machine learning, deep ...