The FETA project has produced a variety of results, including hardware and software components, datasets, and methodologies for network traffic analysis. Below is a summary of the key results.

Result	Type	Description	Link
V1	Hardware platform	NDK platform – generic FPGA framework used as a foundation for network probe firmware	GitHub
V1	Software platform	NDK platform – software framework providing basic components for applications on network probes	GitHub
V1	Conversion tool	Tool for converting LGBM machine learning models into VHDL for hardware deployment	GitHub
V2	Detection tool	DomainRadar – system for detecting and monitoring malicious domains	GitHub
V2	Detection tool	MalwareRadar – system for detecting malware‑related network traffic	GitHub
V3	Machine learning classifiers	Repository of machine learning classifiers for network traffic analysis	GitHub
V4	Dataset catalog	Katoda – catalog of available network datasets	GitHub
V4	Dataset tools	Tools for working with the dataset catalog	GitHub
V4	Dataset repository	TSZoo – collection of time‑series datasets	GitHub
V4	Dataset repository	DataZoo – collection of network datasets	GitHub
V5	Capture infrastructure	Traffic Capture Infrastructure (TCI) – semi‑automatic system for creating annotated datasets	GitHub