Location
Grand Wailea, Hawaii
Event Website
https://hicss.hawaii.edu/
Start Date
8-1-2019 12:00 AM
End Date
11-1-2019 12:00 AM
Description
The continued adoption of Additive Manufacturing (AM) technologies is raising concerns in the security, forensics, and intelligence gathering communities. These concerns range from identifying and mitigating compromised devices, to theft of intellectual property, to sabotage, to the production of prohibited objects. Previous research has provided insight into the retrieval of configuration information maintained on the devices, but this work shows that the devices can additionally maintain information about the print process. Comparisons between before and after images taken from an AM device reveal details about the device’s activities, including printed designs, menu interactions, and the print history. Patterns in the storage of that information also may be useful for reducing the amount of data that needs to be examined during an investigation. These results provide a foundation for future investigations regarding the tools and processes suitable for examining these devices.
Investigating 3D Printer Residual Data
Grand Wailea, Hawaii
The continued adoption of Additive Manufacturing (AM) technologies is raising concerns in the security, forensics, and intelligence gathering communities. These concerns range from identifying and mitigating compromised devices, to theft of intellectual property, to sabotage, to the production of prohibited objects. Previous research has provided insight into the retrieval of configuration information maintained on the devices, but this work shows that the devices can additionally maintain information about the print process. Comparisons between before and after images taken from an AM device reveal details about the device’s activities, including printed designs, menu interactions, and the print history. Patterns in the storage of that information also may be useful for reducing the amount of data that needs to be examined during an investigation. These results provide a foundation for future investigations regarding the tools and processes suitable for examining these devices.
https://aisel.aisnet.org/hicss-52/st/cyber_threat_intelligence/7