Bit t-SNI Secure Multiplication Gadget for Inner Product Masking
DOI:
https://doi.org/10.46586/tches.v2025.i1.104-127Keywords:
Inner Product Masking, Masking, Non-interference, Probing Security, Side-channel Analysis, SoftwareAbstract
Masking is a sound countermeasure to protect against differential power analysis. Since the work by Balasch et al. in ASIACRYPT 2012, inner product masking has been explored as an alternative to the well known Boolean masking. In CARDIS 2017, Poussier et al. showed that inner product masking achieves higherorder security versus Boolean masking, for the same shared size, in the bit-probing model. Wang et al. in TCHES 2020 verified the inner product masking’s security order amplification in practice and proposed new gadgets for inner product masking. Finally, Wu et al. in TCHES 2022 showed that this security amplification comes from the bit-probing model, but that Wang et al.’s gadgets are not higher-order bitprobing secure reducing the computation’s practical security. The authors concluded their work with the open question of providing an inner product multiplication gadget which maintains the masking’s bit-probing security, and conjectured that such gadget maintains the practical security order amplification of the masking during its computation.
In this paper, we answer positively to Wu et al.’s open problems. We are the first to present a multiplication gadget for inner product masking which is proven secure in the bit-level probing model using the t-Strong Non-Interference (SNI) property. Moreover, we provide practical evidence that the gadget indeed maintains the security amplification of its masking. This is done via an evaluation of an assembly implementation of the gadget on an ARM Cortex-M4 core. We used this implementation to take leakage measurements and show no leakage happens for orders below the gadget’s bit-probing security level either for its univariate or multivariate analysis.
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Copyright (c) 2024 John Gaspoz, Siemen Dhooghe
This work is licensed under a Creative Commons Attribution 4.0 International License.