Discover why AI detection software struggles to identify student cheating. Explore the technological arms race in academic ...

Network intrusion detection and pattern matching techniques form a critical pillar in contemporary cybersecurity. These methods enable the identification of malicious activities by scrutinising ...

Explore how AI-driven anomaly detection enhances the security of Model Context Protocol (MCP) deployments, protecting AI infrastructure from evolving threats with real-time insights.

Cintas, Celia, Skyler Speakman, Girmaw Abebe Tadesse, Victor Akinwande, Edward McFowland III, and Komminist Weldemariam. "Pattern Detection in the Activation Space for Identifying Synthesized Content.

McFowland III, Edward, Skyler Speakman, and Daniel B. Neill. "Fast Generalized Subset Scan for Anomalous Pattern Detection." Art. 12. Journal of Machine Learning Research 14 (2013): 1533–1561.

How Search Engines Use Machine Learning for Pattern Detection Algorithm updates like Google Panda are more understandable when you grasp the basics of machine learning. Here’s a simplified breakdown ...

Advanced machine learning is beginning to make inroads into yield enhancement methodology as fabs and equipment makers seek to identify defectivity patterns in wafer images with greater accuracy and ...

Design patterns constitute a fundamental component in the architecture of software systems, providing standardised and reusable solutions to recurring design challenges. Originating from seminal works ...

Kinil Doshi is a Senior VP at Citibank and a fintech expert in banking compliance and risk management with two decades of experience. In this article, I want to explore AI applications in fraud ...

The hyperpersonalization pattern is defined as using machine learning to develop a profile of each individual, and then having that profile learn and adapt over time for a wide variety of purposes ...