Comparing Large-unit and Bitwise Linear Approximations of SNOW 2.0 and SNOW 3G and Related Attacks

IF 1.7 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING
Xinxin Gong, Bin Zhang
{"title":"Comparing Large-unit and Bitwise Linear Approximations of SNOW 2.0 and SNOW 3G and Related Attacks","authors":"Xinxin Gong, Bin Zhang","doi":"10.46586/TOSC.V2021.I2.71-103","DOIUrl":null,"url":null,"abstract":"In this paper, we study and compare the byte-wise and bitwise linear approximations of SNOW 2.0 and SNOW 3G, and present a fast correlation attack on SNOW 3G by using our newly found bitwise linear approximations. On one side, we reconsider the relation between the large-unit linear approximation and the smallerunit/ bitwise ones derived from the large-unit one, showing that approximations on large-unit alphabets have advantages over all the smaller-unit/bitwise ones in linear attacks. But then on the other side, by comparing the byte-wise and bitwise linear approximations of SNOW 2.0 and SNOW 3G respectively, we have found many concrete examples of 8-bit linear approximations whose certain 1-dimensional/bitwise linear approximations have almost the same SEI (Squared Euclidean Imbalance) as that of the original 8-bit ones. That is, each of these byte-wise linear approximations is dominated by a single bitwise approximation, and thus the whole SEI is not essentially larger than the SEI of the dominating single bitwise approximation. Since correlation attacks can be more efficiently implemented using bitwise approximations rather than large-unit approximations, improvements over the large-unit linear approximation attacks are possible for SNOW 2.0 and SNOW 3G. For SNOW 3G, we make a careful search of the bitwise masks for the linear approximations of the FSM and obtain many mask tuples which yield high correlations. By using these bitwise linear approximations, we mount a fast correlation attack to recover the initial state of the LFSR with the time/memory/data/pre-computation complexities all upper bounded by 2174.16, improving slightly the previous best one which used an 8-bit (vectorized) linear approximation in a correlation attack with all the complexities upper bounded by 2176.56. Though not a significant improvement, our research results illustrate that we have an opportunity to achieve improvement over the large-unit attacks by using bitwise linear approximations in a linear approximation attack, and provide a newinsight on the relation between large-unit and bitwise linear approximations.","PeriodicalId":37077,"journal":{"name":"IACR Transactions on Symmetric Cryptology","volume":"40 12","pages":"71-103"},"PeriodicalIF":1.7000,"publicationDate":"2021-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IACR Transactions on Symmetric Cryptology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.46586/TOSC.V2021.I2.71-103","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, SOFTWARE ENGINEERING","Score":null,"Total":0}
引用次数: 2

Abstract

In this paper, we study and compare the byte-wise and bitwise linear approximations of SNOW 2.0 and SNOW 3G, and present a fast correlation attack on SNOW 3G by using our newly found bitwise linear approximations. On one side, we reconsider the relation between the large-unit linear approximation and the smallerunit/ bitwise ones derived from the large-unit one, showing that approximations on large-unit alphabets have advantages over all the smaller-unit/bitwise ones in linear attacks. But then on the other side, by comparing the byte-wise and bitwise linear approximations of SNOW 2.0 and SNOW 3G respectively, we have found many concrete examples of 8-bit linear approximations whose certain 1-dimensional/bitwise linear approximations have almost the same SEI (Squared Euclidean Imbalance) as that of the original 8-bit ones. That is, each of these byte-wise linear approximations is dominated by a single bitwise approximation, and thus the whole SEI is not essentially larger than the SEI of the dominating single bitwise approximation. Since correlation attacks can be more efficiently implemented using bitwise approximations rather than large-unit approximations, improvements over the large-unit linear approximation attacks are possible for SNOW 2.0 and SNOW 3G. For SNOW 3G, we make a careful search of the bitwise masks for the linear approximations of the FSM and obtain many mask tuples which yield high correlations. By using these bitwise linear approximations, we mount a fast correlation attack to recover the initial state of the LFSR with the time/memory/data/pre-computation complexities all upper bounded by 2174.16, improving slightly the previous best one which used an 8-bit (vectorized) linear approximation in a correlation attack with all the complexities upper bounded by 2176.56. Though not a significant improvement, our research results illustrate that we have an opportunity to achieve improvement over the large-unit attacks by using bitwise linear approximations in a linear approximation attack, and provide a newinsight on the relation between large-unit and bitwise linear approximations.
比较SNOW 2.0和SNOW 3G的大单位和位线性逼近及相关攻击
在本文中,我们研究和比较了snow2.0和snow3g的字节线性近似和位线性近似,并利用我们新发现的位线性近似提出了对snow3g的快速相关攻击。一方面,我们重新考虑了大单位线性近似和由大单位近似衍生的小单位/位近似之间的关系,表明在线性攻击中,大单位字母近似比所有小单位/位近似具有优势。但另一方面,通过分别比较SNOW 2.0和SNOW 3G的字节线性近似和位线性近似,我们发现了许多8位线性近似的具体例子,其某些一维/位线性近似与原始8位近似具有几乎相同的SEI(平方欧几里得不平衡)。也就是说,每一个字节线性近似都由单个位近似控制,因此整个SEI本质上并不大于占主导地位的单个位近似的SEI。由于使用位逼近而不是大单位逼近可以更有效地实现相关攻击,因此在SNOW 2.0和SNOW 3G中可以对大单位线性逼近攻击进行改进。对于SNOW 3G,我们对FSM的线性逼近进行了仔细的位掩码搜索,得到了许多具有高相关性的掩码元组。通过使用这些位线性近似,我们安装了一个快速相关攻击来恢复LFSR的初始状态,时间/内存/数据/预计算复杂性的上界为2174.16,略微改进了之前使用8位(矢量化)线性近似的相关攻击,所有复杂性的上界为2176.56。虽然没有显著的改进,但我们的研究结果表明,我们有机会通过在线性近似攻击中使用位线性近似来实现对大单位攻击的改进,并为大单位和位线性近似之间的关系提供了新的视角。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
IACR Transactions on Symmetric Cryptology
IACR Transactions on Symmetric Cryptology Mathematics-Applied Mathematics
CiteScore
5.50
自引率
22.90%
发文量
37
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信