Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Governing the Future: Federal Cybersecurity in the Age of Edge and AI

Intel's CTO on Navigating Cybersecurity, AI, and the Edge Governing the Future: Federal Cybersecurity in the Age of Edge and AI In this episode of the "Trusted Tech for Critical Missions" podcast, host Ben Arent interviews Steve Orrin, Chief Technology Officer at Intel Federal, about the evolving landscape of federal cybersecurity in the age of edge computing and artificial intelligence. Key Takeaways.

CrowdStrike + Fortinet: Unifying AI-Native Endpoint and Next-Gen Firewall Protection

In today’s fast-evolving cybersecurity landscape, organizations face an increasing barrage of sophisticated threats targeting endpoints, networks and every layer in between. CrowdStrike and Fortinet have formed a powerful partnership to deliver industry-leading protection from endpoint to firewall.

LLM Guardrails: Secure and Accurate AI Deployment

Deploying large language models (LLMs) securely and accurately is crucial in today’s AI deployment landscape. As generative AI technologies evolve, ensuring their safe use is more important than ever. LLM guardrails are essential mechanisms designed to maintain the safety, accuracy, and ethical integrity of these models. They prevent issues like misinformation, bias, and unintended outputs.

How to Safely Integrate LLMs Into Enterprise Applications and Achieve ISO 42001 Compliance

Enterprise applications, whether on-premise or in the cloud, access LLMs via APIs hosted in public clouds. These applications might be used for content generation, summarization, data analysis, or a plethora of other tasks. Riscosity’s data flow posture management platform protects sensitive data that would otherwise be accessible to LLM integrations.

Emerging AI Use Cases in Healthcare: A Comprehensive Overview

The integration of AI, especially Gen AI, into healthcare has been transforming the industry, enabling providers to enhance patient care, streamline operations, and reduce costs. Below is an overview of the most promising AI use cases in healthcare that are reshaping the industry.

How to Detect Threats to AI Systems with MITRE ATLAS Framework

Cyber threats against AI systems are on the rise, and today’s AI developers need a robust approach to securing AI applications that address the unique vulnerabilities and attack patterns associated with AI systems and ML models deployed in production environments. In this blog, we’re taking a closer look at two specific tools that AI developers can use to help detect cyber threats against AI systems.