Techniques to Camouflage and Deceive AI/ML or Autonomous Systems on the Battlefield


Posted on October 5, 2021 | Completed on August 12, 2021 | By: Richard Piner, Doyle T. Motes III

What techniques of camouflage and deception are effective against AI/ML or autonomous systems on the battlefield?

The Defense Systems Information Analysis Center (DSIAC) was asked to research techniques for defeating adversary artificial intelligence/machine learning (AI/ML) target recognition. AI/ML research is driving the advancement of the next generation of automatic target recognition (ATR) capabilities using electro-optical infrared (EO/IR) sensors. The inquirer was seeking to develop and field robust AI/ML-based ATR algorithms and, at the same time, recognized that it is critical to develop concealment and deception technologies to protect against peer and near-pear adversaries’ AI/ML ATR capabilities. DSIAC subject matter experts identified and compiled findings on a variety of options from open sources, including flooding the light source; using near-infrared light, retroreflectors, and masking; and using specialized images to confuse AI/ML, labeling, and future camouflage options.

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