Artificial intelligence (AI) has rapidly emerged as the double-edged sword of the cyber threat environment. Sophisticated AI ...

Based on this, an attack detection and localization framework for data-driven design of DC-MG system is presented. The proposed framework includes a bank of adaptive residual generators, adaptive ...

Sonatype’s Open Source Malware Index draws from its proprietary behavioral and automated malware detection systems, actively monitoring and analyzing activity across ecosystems such as npm, PyPI ...

Inkjet printing of π-conjugated organic compounds enabled rapid, low-cost generation of training images for the image-based machine learning (ML) prediction of mixing ratios. ML models with mean ...

Improve this page Add a description, image, and links to the signature-based-detection topic page so that developers can more easily learn about it.

The application of Deep Learning-based Schemes (DLSs) for detecting False Data Injection Attacks (FDIAs) in smart grids has attracted significant attention. This paper demonstrates that adversarial ...

Traditional defenses—whether signature-based detection, static rules or first-generation ML models—while effective against known threats, struggle with the scale and complexity of modern ...

SOCs face evolving cyber threats as 80% of attacks mimic user behavior. Discover how multi-layered NDR detection strategies enhance defense.