Using generative AI to design, train, or perform steps within a machine-learning system is risky, argues computer scientist Micheal Lones in a paper appearing in Patterns. Though large language models ...

The results show that the Decision Tree model emerged as the top-performing algorithm, achieving an accuracy rate of 99.36 percent. Random Forest followed closely with 99.27 percent accuracy, while ...

In today’s digital landscape, cyber threats are evolving at an unprecedented pace. Traditional security measures struggle to ...

Gartner has predicted that by 2030, over 50 per cent of IT security spending will be allocated to pre-emptive cybersecurity ...

Traditional security setups focus on walls around your network. They block outsiders at the gate. But intelligent cloud apps run AI and ML ...

The Microsoft Defender Security Research Team uncovered a sophisticated macOS intrusion campaign attributed to the North ...

Machine learning is helping cyber teams process telemetry at scale to more quickly identify behavioral anomalies that might ...

In the SOC of the future, autonomous defense moves at machine speed, agents add context and coordination, and humans focus on ...

Cyber threats are increasing in speed and complexity, driving the need for advanced detection techniques. Machine learning is transforming how organizations anticipate and counter cyber attacks.

Researchers in Morocco analyzed cybersecurity challenges in smart grids, highlighting AI-driven detection and defense strategies against threats like distributed denial-of-service, false data ...

Researchers have uncovered a new malware strain capable of stealing credentials immediately after gaining a foothold on a victim network, capturing both stored browser passwords and live keystrokes in ...

This project is a comprehensive malware detection system developed as part of a semester project. It combines machine learning with web technologies to provide safe, static analysis of executable ...