An Efficient Random Forest Classifier for Detecting Malicious Docker Images in Docker Hub Repository
Abstract: The number of exploits of Docker images involving the injection of adversarial behaviors into the image’s layers is increasing immensely. Docker images are a fundamental component of Docker.
New research tries to anticipate road building to identify areas in the Amazon, Asia and Africa that are likely to face ...
A research team introduces a hierarchical Bayesian spatial approach that integrates UAV and terrestrial LiDAR data to estimate AGB of individual trees in natural secondary forests of northeastern ...
Abstract: Packet classification is an essential function for many applications such as QoS provisioning and network intrusion detection. In this work, we perform random forest classification in the ...
Accurately quantifying forest volume and identifying its driving mechanisms are critical for achieving carbon neutrality objectives. Using data from the National Forest Inventory (NFI), plot-level ...
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