In today's digital world, everything from medical images and financial records to personal photos and secure communications depends on encryption systems that can protect sensitive information. But real-world technologies rarely operate under perfect conditions. Measurements can be imprecise, hardware introduces small errors, and communication channels are often affected by noise.
Mathematical model makes image encryption more resilient to real-world uncertainty
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