Floating-point weight formats in embedded neural networks suffer near-total accuracy loss from a single electromagnetic fault injection, while 8-bit integer formats retain substantially higher accuracy on the same hardware.
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2026 2verdicts
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A constant-time implementation methodology for activation functions on ARM Cortex-M4 microcontrollers using branchless selection, Padé approximations, dummy arithmetic, and cycle alignment to eliminate timing side channels while preserving accuracy.
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The Weight of a Bit: EMFI Sensitivity Analysis of Embedded Deep Learning Models
Floating-point weight formats in embedded neural networks suffer near-total accuracy loss from a single electromagnetic fault injection, while 8-bit integer formats retain substantially higher accuracy on the same hardware.
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A Constant-Time Implementation Methodology for Activation Functions on Microcontrollers
A constant-time implementation methodology for activation functions on ARM Cortex-M4 microcontrollers using branchless selection, Padé approximations, dummy arithmetic, and cycle alignment to eliminate timing side channels while preserving accuracy.