New report recognizes Lumu Defender's unified detection and response built for today’s modern enterprise infrastructure spanning on-premises, hybrid, and cloud. Lumu achieved the highest ...

This project implements a system for detecting anomalies in time series data collected from Prometheus. It uses an LSTM (Long Short-Term Memory) autoencoder model built with TensorFlow/Keras to learn ...

Internet of Vehicles (IoV) systems, while offering significant advancements in transportation efficiency and safety, introduce substantial security vulnerabilities due to their highly interconnected ...

A comprehensive simulation-based anomaly detection system for Wireless Sensor Networks (WSNs) using temperature, motion, and pulse sensors. The system detects 5 types of anomalies (DoS, jamming, ...

Spectral Unmixing is an important technique in remote sensing for analyzing hyperspectral images to identify endmembers and estimate fractional abundance maps. Over the past few decades, significant ...

Leader in cryptocurrency, Bitcoin, Ethereum, XRP, blockchain, DeFi, digital finance and Web 3.0 news with analysis, video and live price updates.

Deep neural networks are more suited to extract prospective features from 2D spectrograms than time-domain neural networks because it can more quickly acquire specific contextual information. To apply ...

W. Shin, S. Bu and S. Cho, 3D-convolutional neural network with generative adversarial network and autoencoder for robust anomaly detection in video surveillance, Int. J. Neural Syst. 30(6) (2020) ...