Abstract
The physical randomness of the flying capacitors in the multi-phase on-chip switched-capacitor (SC) voltage converter is exploited as a novel strong physical unclonable function (PUF) primitive for IoT authentication. Moreover, for the strong PUF we devised, an approximated constant input power is achieved against side-channel attacks and a non-linear transformation block is utilized to scramble the high linear relationship between the input challenges and output responses against machine-learning attacks. The results show that the novel strong PUF primitive we designed achieves a nearly 51.3% inter-Hamming distance (HD) and 98.5% reliability while maintaining a high security level against both side-channel and machine-learning attacks.
Original language | English (US) |
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Pages (from-to) | 587-598 |
Number of pages | 12 |
Journal | Journal of Electronic Testing: Theory and Applications (JETTA) |
Volume | 34 |
Issue number | 5 |
DOIs | |
State | Published - Oct 1 2018 |
Keywords
- Machine-learning attacks
- Multi-phase
- Side-channel attacks
- Strong physical unclonable function (PUF) primitive
- Voltage converter