Artificial intelligence (AI) and machine learning (ML) are predicted to have a significant impact on future industrial cybersecurity. They can help monitor network traffic in real-time to detect ...

In this special edition, Tenable leaders forecast key 2026 trends, including: AI will make attacks more plentiful and less costly; machine identities will become the top cloud risk; preemptive cloud ...

TNO’s methodologies and tools embed autonomous cyber resilience (ACR) into critical digital systems for improved resilience ...

That’s the aim of predictive cyber resilience (PCR)—an emerging approach to security built on intelligence, automation and adaptability. It introduces a vision of self-defending systems capable of ...

Phoenix Contact, Softing and Mitsubishi/Iconics show how basic best practices provide a solid foundation for cybersecurity ...

Expect significant innovations in AI-driven cyber tools and a closer convergence between cybersecurity and geopolitics, they ...

With the increasing use of automated systems comes a greater risk of outside threats interfering with critical operations. Digitization engenders the threat that systems can be compromised, and new ...

Demonstrating and applying control theory has long presented a complex challenge, encompassing a broad range of engineering ...

Outlining real-world attacks against the water, oil and gas, and agriculture industries, Canada’s Centre for Cyber Security highlights the risks of internet-exposed ICS devices. Security experts have ...

From AI ministers to cyber risk at scale, 2026 marks a turning point as governments embed AI into systems that underpin trust ...

The spectacular, but ultimately harmless, hacking of the My Volkswagen app by an Indian cyber researcher last year continues to raise serious questions about cyber security for millions of connected ...