Second-Order Masked Lookup Table Compression Scheme

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 m...

Full description

Bibliographic Details
Main Authors: Annapurna Valiveti, Srinivas Vivek
Format: Article
Language:English
Published: Ruhr-Universität Bochum 2020-08-01
Series:Transactions on Cryptographic Hardware and Embedded Systems
Subjects:
Online Access:https://tches.iacr.org/index.php/TCHES/article/view/8679
id doaj-f0a5999c554d43b59dd0baf05e35fe24
record_format Article
spelling doaj-f0a5999c554d43b59dd0baf05e35fe242020-11-25T03:52:51ZengRuhr-Universität BochumTransactions on Cryptographic Hardware and Embedded Systems2569-29252020-08-012020410.13154/tches.v2020.i4.129-153Second-Order Masked Lookup Table Compression SchemeAnnapurna Valiveti0Srinivas Vivek1IIIT Bangalore, IndiaIIIT Bangalore, India 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. https://tches.iacr.org/index.php/TCHES/article/view/8679MaskingS-boxTable compressionProbing leakage modelSNI securitySide-channel attacks
collection DOAJ
language English
format Article
sources DOAJ
author Annapurna Valiveti
Srinivas Vivek
spellingShingle Annapurna Valiveti
Srinivas Vivek
Second-Order Masked Lookup Table Compression Scheme
Transactions on Cryptographic Hardware and Embedded Systems
Masking
S-box
Table compression
Probing leakage model
SNI security
Side-channel attacks
author_facet Annapurna Valiveti
Srinivas Vivek
author_sort Annapurna Valiveti
title Second-Order Masked Lookup Table Compression Scheme
title_short Second-Order Masked Lookup Table Compression Scheme
title_full Second-Order Masked Lookup Table Compression Scheme
title_fullStr Second-Order Masked Lookup Table Compression Scheme
title_full_unstemmed Second-Order Masked Lookup Table Compression Scheme
title_sort second-order masked lookup table compression scheme
publisher Ruhr-Universität Bochum
series Transactions on Cryptographic Hardware and Embedded Systems
issn 2569-2925
publishDate 2020-08-01
description 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.
topic Masking
S-box
Table compression
Probing leakage model
SNI security
Side-channel attacks
url https://tches.iacr.org/index.php/TCHES/article/view/8679
work_keys_str_mv AT annapurnavaliveti secondordermaskedlookuptablecompressionscheme
AT srinivasvivek secondordermaskedlookuptablecompressionscheme
_version_ 1724480599830298624