Researchers have demonstrated an explainable machine learning ensemble combining XGBoost and a multilayer perceptron that achieved 99.3 percent intrusion detection ...
Researchers have developed a behavioural intrusion detection framework that integrates with standard medical access control systems to identify covert cyberattacks ...
A new study presents HPQ-EAI-IDS, a unified intrusion detection system for IoT networks that combines explainable AI, post-quantum security, and ...
A new distributed intrusion detection system uses machine learning, blockchain and collaborating fog nodes, with reported zero-day F1-score rising from ...
A new review organises side-impact protection of floor-mounted EV battery packs into redirect, absorb and redistribute layers and warns that ...
Researchers have introduced CAE-IDS, an intrusion detection framework that pairs a Concrete Autoencoder-based feature selection mechanism with Bayesian hyperparameter optimization, ...
A new study reports that changing how intrusion detection data is prepared before it reaches an AI model can lift ...
In a computational evaluation on 5G-NIDD, a deep autoencoder trained only on benign flows and thresholded with an adaptive IQR ...
Groundwater managers have long assumed that seawater intrusion fades predictably with distance from the shoreline. A new study of the ...
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