Why AI Threat Models In Finance Must Follow The Data, Not The Code

For financial institutions, threat modeling must shift away from diagrams focused purely on code to a life cycle view ...
Security Boulevard

User and Entity Behavior Analytics: The Intelligence Layer for Modern Cybersecurity

Traditional security measures like firewalls and antivirus software are no longer sufficient to protect organizations from ...
Morning Overview on MSN

Scientists build a ‘periodic table’ for AI models

Scientists are trying to tame the chaos of modern artificial intelligence by doing something very old fashioned: drawing a ...
2UrbanGirls on MSN

Jimmy Joseph honored with a 2025 global recognition award for an AI breakthrough that strengthened payment integrity for millions in the USA

Jimmy Joseph, senior solutions engineer at a Fortune 500 healthcare company, received a 2025 Global Recognition Award fo ...
Analytics Insight

How to Detect AI-Generated Music?

As AI Music Tools Proliferate, Detection Technologies and Industry Responses EvolveThe music industry faces an unprecedented ...
Security Boulevard

AI-Driven Anomaly Detection for MCP Security.

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.
IEEE

Anomaly Detection in IoT Networks: A Deep Learning Approach Using Autoencoders

Abstract: The current fast proliferation of the Internet of Things (IoT) networks has made anomaly detection and security more difficult. Traditional methods are not able to detect hostile activities ...
The Debrief

Bermuda Mystery Surfaces with Discovery of Massive Underground Structure, Revealing a New Deep-Earth Anomaly

A new seismic analysis has revealed an unusually thick structure beneath Bermuda, a geological oddity that defies conventional models and may rewrite scientists’ understanding of how the island chain ...
IEEE

Hyperspectral Anomaly Detection Using Dual-Branch Network Based on Frequency Domain Learning

Abstract: Existing deep learning-based hyperspectral anomaly detection methods often overlook frequency domain features, hindering the ability to effectively distinguish between background and ...