A Security Agent for Your Network? Reinforcement Learning for Detecting Anomalies in Network Traffic
Our daily lives are becoming increasingly digital, and computer networks continue to grow in both size and complexity. The traffic they carry is becoming denser and more diverse: banking transactions, health data, private communications, etc.
With the rise of so-called intelligent technologies — smart homes, smart cities, personalized medicine — the number of connected devices is expected to exceed 50 billion by the end of 2025. These devices, though ubiquitous, are often poorly secured: neglected updates, weak passwords, outdated protocols.
In this context, computer networks are prime targets for cybercriminals, who benefit from an ever-expanding attack surface. Designing effective and robust cybersecurity solutions has thus become a critical challenge — a fast-moving research field, but also an increasingly complex one.