April 20, 2024

New Cyber Protections Against Stealthy “Logic Bombs” Targeting 3D Printed Drones, Prostheses and Medical Devices

Cyber attackers could target 3D printed objects in health care, aerospace, and other fields.

Cybersecurity scientists at Rutgers University-New Brunswick and the Georgia Institute of Technology have actually proposed brand-new methods to secure 3D printed things such as drones, prostheses, and medical devices from sneaky “logic bombs.”.
The scientists will present their paper, titled “Physical Logic Bombs in 3D Printers through Emerging 4D Techniques,” at the 2021 Annual Computer Security Applications Conference on December 10, 2021.
Fast prototyping is the quick fabrication of a model, part or assembly using 3D computer system helped style, generally using 3D printing or “additive production.” Additive manufacturing is increasingly used in a variety of markets to produce safety-critical items, but there presently are no reliable approaches for validating their stability against adversarial pre-print design modifications.
” Next-generation, cyber-physical additive manufacturing allows sophisticated product styles and abilities, but it increasingly counts on extremely networked industrial control systems that present opportunities for cyber-attacks,” said primary private investigator Saman Zonouz, an associate professor of electrical and computer system engineering in the Rutgers-New Brunswick School of Engineering. “The primary technique to safeguarding against these dangers relies on host-based invasion detectors that sit within the exact same target controllers, and hence are often the first target of the controller attacks.”.
The researchers checked out Mystique, a brand-new class of attacks on printed items that leverage emerging 4D printing innovation to introduce ingrained computer code– or reasoning bombs– by controling the production procedure.
Mystique enables aesthetically safe objects to behave maliciously when a reasoning bomb is triggered by a stimulus such as modifications in temperature, moisture, pH or adjustments to the products used initially, potentially triggering devastating operational failures when they are used.
The researchers successfully examined Mystique on numerous 3D printing case research studies and showed that it can avert previous countermeasures. To address this, they proposed two techniques.
The very first option focuses on creating a sensor that can determine the composition and diameter of basic materials passing through the printers extruder to guarantee they satisfy expectations prior to the things is printed. A dielectric sensing unit can find a change of 0.1 mm in filament sizes and a modification of 10% in concentration structure.
The 2nd solution utilizes high-resolution computed tomography images to detect residual tensions in printed objects that contrast malicious and benign designs prior to activation of the attack. This CT detection has a precision of 94.6% in determining 4D attacks in a single printing layer.
The research study group plans to provide standards to loop resilience options in software security, control system design and signal processing, and to incorporate practical and dependable cyber-physical attack detection into real-world production.
” Our proposal is an unique prospective attack vector that needs to be thought about and mitigated efficiently in additive manufacturing platforms. The concept is to use brand-new physical logic bombs in 3D printed things, such as industrial gears and personal protective equipment like COVID-19 masks,” Zonouz said. “These logic bombs can later on be activated by the foes using physical stimulus like wetness or heat whenever appropriate for them to make the printed objects malfunction, such as to make a COVID mask lose its protection against the viral infection.”.
Reference: “Physical Logic Bombs in 3D Printers through Emerging 4D Techniques” by Tuan Le, Sriharsha Etigowni, Sizhuang Liang, Xirui Peng, Jerry Qi, Mehdi Javanmard, Saman Zonouz and Raheem Beyah, 10 December 2021, 2021 Annual Computer Security Applications Conference.
The research was funded by the National Science Foundation.

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