A researcher trained neural networks to detect lateral movement cyberattacks using only synthetic data from simulated corporate networks, then validated the approach against 1.65 billion real authentication logs from Los Alamos National Laboratory. The synthetic-trained models ranked suspicious login windows effectively, identifying real attacks in the top results with far fewer false alarms than traditional threshold methods.
A lightweight anomaly detection daemon (sentinel-imxd) for NXP i.MX 8M Plus boards that monitors systemd journal and D-Bus events, normalizes them into INT8 vectors, and runs TensorFlow Lite autoencoders on the Vivante NPU to detect anomalies via reconstruction loss thresholding, with training on a host Docker environment and deployment via SSH.
Daemon OS is an infrastructure monitoring platform that transforms system telemetry into actionable intelligence by analyzing CPU, memory, and storage metrics to detect anomalies, assess health, and provide recommended actions. It offers tiered pricing from personal to enterprise use, with additional creative tools through Creatorsverse.