CTI-REALM is Microsoft’s open-source benchmark that evaluates AI agents on real-world detection engineering. It measures whether an agent can take cyber threat intelligence (CTI) and produce validated ...
As AI systems grow more autonomous, observability becomes essential. Learn how visibility into AI behavior helps detect risk and strengthen secure development.
Enterprise security teams drown in alerts but struggle to fix known risks. AI agents are changing how organizations remediate ...
Abstract: The Internet of Vehicles (IoV) is highly vulnerable to attacks due to its open communication environment, with new types of attacks continuously emerging. However, existing Network Intrusion ...
ABSTRACT: Local Area Networks (LANs) are critical to organizational infrastructure, yet they remain highly vulnerable to sophisticated cyber threats such as insider misuse, ARP spoofing, privilege ...
This document specifies a machine learning system for network intrusion detection that implements both supervised classification and unsupervised anomaly detection methodologies. The unsupervised ...
Palo Alto Networks (PANW) has expanded its partnership with Google Cloud (GOOG)(GOOGL) as a rising number of cyberattacks target organizations' artificial intelligence systems and cloud infrastructure ...
What’s driving the rise in digital fraud? The global payments landscape appears more dynamic and complex than ever before. As e-commerce spending accelerates toward an estimated $8.1 trillion by 2028, ...
The exponential growth of network-based cyberattacks has increased the demand for accurate and adaptive Network Intrusion Detection Systems (NIDS) [1], [2]. In recent years, Machine Learning (ML) has ...
ABSTRACT: The accelerating sophistication of cyberattacks poses unprecedented challenges for national security, critical infrastructures, and global digital resilience. Traditional signature-based ...
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