International Association for Cryptologic Research

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Paper: Second-Order Masked Lookup Table Compression Scheme

Authors:
Annapurna Valiveti , IIIT Bangalore, India
Srinivas Vivek , IIIT Bangalore, India
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DOI: 10.13154/tches.v2020.i4.129-153
URL: https://tches.iacr.org/index.php/TCHES/article/view/8679
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Abstract: Masking by lookup table randomisation is a well-known technique used to achieve side-channel attack resistance for software implementations, particularly, against DPA attacks. The randomised table technique for first- and second-order security requires about m•2n bits of RAM to store an (n,m)-bit masked S-box lookup table. Table compression helps in reducing the amount of memory required, and this is useful for highly resource-constrained IoT devices. Recently, Vadnala (CT-RSA 2017) proposed a randomised table compression scheme for first- and second-order security in the probing leakage model. This scheme reduces the RAM memory required by about a factor of 2l, where l is a compression parameter. Vivek (Indocrypt 2017) demonstrated an attack against the second-order scheme of Vadnala. Hence achieving table compression at second and higher orders is an open problem.In this work, we propose a second-order secure randomised table compression scheme which works for any (n,m)-bit S-box. Our proposal is a variant of Vadnala’s scheme that is not only secure but also significantly improves the time-memory trade-off. Specifically, we improve the online execution time by a factor of 2n−l. Our proposed scheme is proved 2-SNI secure in the probing leakage model. We have implemented our method for AES-128 on a 32-bit ARM Cortex processor. We are able to reduce the memory required to store a randomised S-box table for second-order AES-128 implementation to 59 bytes.
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BibTeX
@article{tches-2020-30550,
  title={Second-Order Masked Lookup Table Compression Scheme},
  journal={IACR Transactions on Cryptographic Hardware and Embedded Systems},
  publisher={Ruhr-Universität Bochum},
  volume={2020, Issue 4},
  pages={129-153},
  url={https://tches.iacr.org/index.php/TCHES/article/view/8679},
  doi={10.13154/tches.v2020.i4.129-153},
  author={Annapurna Valiveti and Srinivas Vivek},
  year=2020
}