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L_Anti-Spoofing Norm Engineered Recognizer (LASER™) is the result of a research started to give answers to some issues raised in the DARPA GARD (Guaranteeing AI Robustness against Deception) program. The LASER™ classifier can be used as a plug-in for a CNN or in a context where features extraction is executed in a different way.

 

 

Recognition with a state of the art CNN

Recognition with the same CNN after a targeted attack with our GAN for generation of Physically Feasible Deception Patterns (PFDP)

Recognition with a state of the art CNN and a final LASER™ classification layer

With LASER™ technology the GAN failed to converge in the generation of PFDP and in the generation of any spoofing pixels pattern in the full image

 

 

FREE DECEPTION PATTERNS

(easy task for GAN)

 

PHYSICALLY FEASIBLE DECEPTION PATTERNS

(linear increase in complexity)

 

PHYSICALLY CONSTRAINED DECEPTION PATTERNS

(exponential increase in complexity)

 

 

 

 

 

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Email:_luca.marchese@synaptics.org

 

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