Network security has developed as a critical research subject as a result of the Rapid advancements in the development of Internet and communication technologies over the previous decades. The ...

With the rapid development of 6G networks, anomaly detection in network edge intelligence faces significant challenges in system interpretability and trustworthiness. Although machine learning-based ...

Doug Bonderud is an award-winning writer capable of bridging the gap between complex and conversational across technology, innovation and the human condition. By defining a set of normal user and ...

VE3 AI Research publishes a study on synthetic data, magnetic dipole modeling, and unsupervised AI for scalable anomaly ...

Businesses and organizations are under heavier fire than usual from cyberattacks, with 57% of CIOs and CISOs reporting at least one significant cybersecurity incident at their companies. Whether the ...

One key part of Microsoft’s big bet on machine learning is that these technologies need to be democratized, turned into relatively simple-to-understand building blocks that Microsoft’s developer ...

What is explainable AI (XAI)? What are some of the use cases for XAI? What are the technology requirements for implementing XAI? Anomaly detection is the process of identifying when something deviates ...

Anomaly detection is one of the more difficult and underserved operational areas in the asset-servicing sector of financial institutions. Broadly speaking, a true anomaly is one that deviates from the ...

Machine learning isn’t a silver bullet for network security. I know, right now you’re saying “But wait Matt, All I hear is that every hot new company in the space is based on machine learning and that ...

Automobiles are now more connected than ever. Not only can they communicate with other vehicles and inanimate objects, but fully autonomous vehicles are potentially around the corner (if there are no ...