Abstract: The escalating diversity of Internet of Things (IoT) devices has intensified security challenges, as signature-based and heavyweight machine learning (ML) defenses often fall short in ...
Due to the complexity of hotel operation processes, abnormal situations are inevitable, making proactive anomaly prediction essential for ensuring operational stability. Although current deep learning ...
Dr. James McCaffrey presents a complete end-to-end demonstration of anomaly detection using k-means data clustering, implemented with JavaScript. Compared to other anomaly detection techniques, ...
This repository contains the source code, scripts, and supplementary materials for the paper: "A New Hybrid Model for Improving Outlier Detection Using Combined Autoencoder and Variational Autoencoder ...
YouTube revealed on Tuesday that its likeness-detection technology has officially rolled out to eligible creators in the YouTube Partner Program, following a pilot phase. The technology allows ...
CSC Digital Brand Services Announces Integration into CrowdStrike Falcon Adversary Intelligence’s Recon to Accelerate Detection and Enforcement Against Malicious Domains CSC, the world’s leading ...
ABSTRACT: This work presents an innovative Intrusion Detection System (IDS) for Edge-IoT environments, based on an unsupervised architecture combining LSTM networks and Autoencoders. Deployed on ...
The datasets were generated using Omnet++, a network simulation tool. It can be used for testing adversarial anomaly detection applications (integrity attacks). Data Type: Multivariate Task: ...
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