J. Todd McDonald

Daniel Bradford Miller, Jacob Gatlin, William Bradley Glisson et al.

The continued adoption of Additive Manufacturing 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.

Patrick Luckett, J Todd McDonald, William Bradley Glisson

The continued integration of technology into all aspects of society stresses the need to identify and understand the risk associated with assimilating new technologies. This necessity is heightened when technology is used for medical purposes like ambulatory devices that monitor a patient's vital signs. This integration creates environments that are conducive to malicious activities. The potential impact presents new challenges for the medical community. Hence, this research presents attack graph modeling as a viable solution to identifying vulnerabilities, assessing risk, and forming mitigation strategies to defend ambulatory medical devices from attackers. Common and frequent vulnerabilities and attack strategies related to the various aspects of ambulatory devices, including Bluetooth enabled sensors and Android applications are identified in the literature. Based on this analysis, this research presents an attack graph modeling example on a theoretical device that highlights vulnerabilities and mitigation strategies to consider when designing ambulatory devices with similar components.

Mark Yampolskiy, Todd R. Andel, J. Todd McDonald et al.

Additive Layer Manufacturing (ALM), also broadly known as 3D printing, is a new technology to produce 3D objects. As an opposite approach to the conventional subtractive manufacturing process, 3D objects are created by adding thin material layers over layers. Until recently, they have been used, mainly, for plastic models. However, the technology has evolved making it possible to use high-quality printing with metal alloys. Agencies and companies like NASA, ESA, Boeing, Airbus, etc. are investigating various ALM technology application areas. Recently, SpaceX used additive manufacturing to produce engine chambers for the newest Dragon spacecraft. BAE System plans to print on-demand a complete Unmanned Aerial Vehicle (UAV), depending on the operational requirements. Companies expect the implementation of ALM technology will bring a broad variety of technological and economic benefits. This includes, but not limited to, the reduction of the time needed to produce complex parts, reduction of wasted material and thus control of production costs along with minimization of part storage space as companies implement just-in-time and on-demand production solutions. The broad variety of application areas and a high grade of computerization of the manufacturing process will inevitably make ALM an attractive target for various attacks.