Defense Cyber Security Market to Progress as Researchers Create a Technique to Defend against Logic Bombs

Posted On May 23, 2022     

Additive printing is rapidly being utilized to create safety-critical items in various industries. However, there are currently no efficient approaches that would help evaluate their integrity against adversarial pre-print design alterations. Next-generation, cyber-physical additive manufacturing allows for more complex product designs and capabilities, but it is becoming increasingly reliant on highly networked industrial control systems, which can be vulnerable to cyber-attacks.

Researchers have now developed a method to defend 3D printed products such as drones, prostheses, and medical devices from stealthy "logic bombs." This may advance the Defence Cyber Security Market, allowing manufacturers to deploy an approach against malicious attacks that previously could not be fought.

The researchers have put forward Mystique, a new type of printed-object attack that uses emerging 4D printing technology to install embedded computer code (logic bombs) by tampering with the production procedure. Whenever a logic bomb is triggered by a stimulus like changes in temperature, moisture, pH, or modifications to the materials used initially, Mystique causes visually normal objects to behave maliciously, potentially causing catastrophic operational failures when they are employed. Mystique was successfully tested on numerous 3D printing case studies, demonstrating that it can elude previous countermeasures. They offered two techniques to address this.

The first approach focuses on developing a sensor that can determine the composition and diameter of raw materials moving through the printer's extruder to verify they fit specifications before the product is created. A dielectric sensor can detect changes in filament widths of 0.1mm and changes in concentration composition of 10%.

The second technique compares benign and malicious designs using high-resolution computed tomography scans to detect residual stresses in printed objects before the assault is launched. The team's CT detection accuracy in identifying 4D attacks in a single printing layer is 94.6 percent.

The study aims to provide guidelines for tying together signal processing, control system design, and resilience solutions in software security. Further, it aims to include reliable and effective cyber-physical attack detection into real-world production.

The researcher's proposal is a first-of-its-kind potential attack vector that should be evaluated and appropriately neutralized in additive manufacturing platforms. The objective is to embed physical logic bombs in personal protective equipment like COVID-19 masks and 3D printed industrial gear. Opponents can then detonate these logic bombs at any time by employing physical stimuli such as moisture or heat to cause the printed products to malfunction, such as causing a COVID mask to lose its viral infection protection.

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