A new family of Android click-fraud trojans leverages TensorFlow machine learning models to automatically detect and interact ...

AI-based security detection automates the analysis of large, complex data sets to uncover threats in real time. These systems not only flag potential risks but can also trigger automated response ...

Intrusion detection systems, long constrained by high false-positive rates and limited adaptability, are being re-engineered ...

Attackers are increasingly abandoning noisy, direct attacks in favor of more subtle, stealthy tactics. They are flying under ...

PropellerAds delivers billions of impressions across more than 195 countries, which exposes the network to significant ...

Amirali Aghazadeh receives funding from Georgia Tech. When NASA scientists opened the sample return canister from the OSIRIS-REx asteroid sample mission in late 2023, they found something astonishing.

Cloud security is not something SMBs can outsource entirely. Vendors secure the infrastructure, but it’s up to businesses to ...

That challenge is examined in the study Towards Eco-Friendly Cybersecurity: Machine Learning-Based Anomaly Detection with ...

Researchers from Stony Brook University, in collaboration with Ecosuite and Ecogy Energy, have developed a self-supervised machine-learning algorithm designed to identify physical anomalies in solar ...

As businesses continue their digital transformation journeys, they are exposed to an ever-expanding attack surface. With the proliferation of cloud environments, remote work, and the increasing use of ...