BotNet Detection

Botnet detection focuses on identifying and mitigating malicious networks of compromised computers controlled by attackers. Current research emphasizes robust machine learning models, including deep learning architectures like LSTM networks and graph neural networks, to detect botnet activity, often focusing on improving resilience against adversarial attacks using techniques like generative adversarial networks (GANs) and conformal prediction. This field is crucial for cybersecurity, as effective botnet detection is vital for protecting critical infrastructure and individual users from various cybercrimes, and ongoing research aims to improve detection accuracy and reduce false positives.