A Taxonomy for Contrasting Industrial Control Systems Asset Discovery Tools - Samanis, Manolis (Cranfield University, 2022)
The number of tools for scanning industrial assets has grown considerably over the past decade. There is currently a plethora of free and commercial asset scanning tools which specialize in industrial control system (ICS) devices. However, to the best of our knowledge, there is no information pertaining to their actual capabilities and no experimental comparative comparison of their features. Moreover, it is not clear to what depth of scanning these tools can reach and whether the tools are suitable to use in a scaled industrial network architecture. This poster provides the first systematic features comparison available on free to use asset scanning tools, on the basis of an ICS scanning taxonomy we propose. Based on the taxonomy, we investigate tools scanning depth and validate results through experimentation on Siemens and Allen Bradley devices.
Keywords: Asset scanning; Industrial control systems; SCADA; DSDS22; DSDS22 Poster