Enterprises are racing to embed large language models (LLMs) into critical workflows ranging from contract review to customer support. But most organizations remain wedded to perimeter-based security ...

Data drift happens when the statistical properties of a machine learning (ML) model's input data change over time, eventually rendering its predictions less accurate. Cybersecurity professionals who ...

Traditionally, enterprise security operating models operated a fixed and regular cycle: Findings surfaced through periodic scans, security teams triaged results and remediation followed through ticket ...

One malicious prompt gets blocked, while ten prompts get through. That gap defines the difference between passing benchmarks and withstanding real-world attacks — and it's a gap most enterprises don't ...

As companies rush to develop and test artificial intelligence and machine learning (AI/ML) models in their products and daily operations, the security of the models is often an afterthought, putting ...

Anand Kashyap is CEO and cofounder of Fortanix, a global leader in data security and a pioneer of confidential computing. AI is becoming a core component of infrastructure for many organizations, ...

A new report on the security of artificial intelligence large language models, including OpenAI LP’s ChatGPT, shows a series of poor application development decisions that carry weaknesses in ...

The company said White House review of AI releases shouldn’t become the norm.

With systems only growing more sophisticated, the potential for new semiconductor vulnerabilities continues to rise. Consumers and hardware partners are counting on organizations meeting their due ...

How does security apply to Cloud Computing? In this article, we address this question by listing the five top security challenges for Cloud Computing, and examine some of the solutions to ensure ...