A team of researchers at Rice University and Baylor College of Medicine has developed a new strategy for identifying ...

a domain where conventional machine learning approaches fail. Unlike many previous methods, the model is trained on real-world data instead of simulations. “It sets a precedent for using real, scarce ...

Although machine learning (ML) techniques have advanced malware ... examples using GANs, then optimizes them through a GA to maximize evasion and minimize noise. Experiments on the VirusShare and ...

Cybercriminals are constantly finding new ways to steal your data. As people become ... hackers are using USB drives to spread malware in ways that can easily bypass traditional security systems.

AML Checker detection and analysis tools for cryptocurrency transactions using machine learning and blockchain data. Ensuring compliance and reducing money laundering risks.

China has issued a guideline to facilitate and regulate cross-border flow of financial data amid efforts to boost high-standard opening up of the financial sector, the central bank said Thursday.

"Machine learning algorithms can label data much faster than ... making fraud detection more efficient." The method combines two strategies: an ensemble of three unsupervised learning techniques using ...

Benedict has spent over 7 years writing about security issues, covering everything from major data ... malware removal programs are also employing artificial intelligence and machine learning ...

The operational principle is analyzed to coordinate the current modulation and machine learning. The experimental results using 800-W prototype DC-DC converter can verify the arc fault detection and ...

Malware🦠 Detection and Analysis using Machine Learning (MDAML) is designed to provide users with an intuitive interface for analyzing and detecting malware in various file formats.