Tag: zero-day attacks

Most intrusion detection research is tested on artificially balanced datasets, where attack and benign records appear in equal numbers. A ...

A new distributed intrusion detection system uses machine learning, blockchain and collaborating fog nodes, with reported zero-day F1-score rising from ...

A systematic review of 120 papers finds deep learning DDoS detectors excel in experiments but struggle in real-world cloud environments, ...

A new framework called TinyRoute combines TinyML, reinforcement learning, and few-shot learning to achieve adaptive routing and zero-day attack detection ...

Researchers built the first public RISC-V dataset combining hardware performance counters with instruction traces and showed that simple tree-based models ...

A new review of 29 recent studies finds that no deep learning intrusion detection system has been evaluated jointly for ...

A new federated learning framework called FedCAMP-IDS detects known and zero-day cyberattacks across heterogeneous IoT networks with up to 99.16 ...

A new study shows that adaptively fusing a closed-world classifier with an unsupervised open-set detector significantly improves detection of zero-day ...