Statistical cryptanalysis of seven classical lightweight ciphers

Runa Chatterjee, Rajdeep Chakraborty
{"title":"Statistical cryptanalysis of seven classical lightweight ciphers","authors":"Runa Chatterjee, Rajdeep Chakraborty","doi":"10.1007/s41870-024-02175-4","DOIUrl":null,"url":null,"abstract":"<p>The smart world currently employs smart devices that are inextricably linked with everyday life. These smart devices are lightweight due to their small size, low memory capacity, low-power batteries, and limited computational capability.Conventional cryptographic algorithms aren’t applicable there. This demand leads to the development of lightweight cryptography (LWC). In various literature surveys, many researchers analysed lightweight ciphers in terms of area, throughput, latency, power consumption, energy dissipation, encryption-decryption time, etc. However, no single paper includes a variety of statistical cryptanalysis of LWCs. Such a type of bit-level data analysis checks the vulnerabilities of algorithms against different kinds of attacks. It ensures the difficulties of cryptanalysis. This paper has included seven classical lightweight ciphers PRESENT, SIMON, TEA, SPECK, CLEFIA, MICKEY2.0, and GRAIN V1, for statistical data analysis. The analysis includes non-homogeneity, avalanche ratio, entropy, floating frequency, frequency distribution, auto-correlation, periodicity, 4-gram pattern analysis.Moreover, four randomness like frequency, serial, run, and poker tests are also added. Finally, a comparative and compact discussion has made on ciphers’ efficiency. This study makes a trade-off, which proves the uniqueness of this work. It opens a new window for the upcoming researchers to search their work area.</p>","PeriodicalId":14138,"journal":{"name":"International Journal of Information Technology","volume":"50 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Information Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s41870-024-02175-4","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

The smart world currently employs smart devices that are inextricably linked with everyday life. These smart devices are lightweight due to their small size, low memory capacity, low-power batteries, and limited computational capability.Conventional cryptographic algorithms aren’t applicable there. This demand leads to the development of lightweight cryptography (LWC). In various literature surveys, many researchers analysed lightweight ciphers in terms of area, throughput, latency, power consumption, energy dissipation, encryption-decryption time, etc. However, no single paper includes a variety of statistical cryptanalysis of LWCs. Such a type of bit-level data analysis checks the vulnerabilities of algorithms against different kinds of attacks. It ensures the difficulties of cryptanalysis. This paper has included seven classical lightweight ciphers PRESENT, SIMON, TEA, SPECK, CLEFIA, MICKEY2.0, and GRAIN V1, for statistical data analysis. The analysis includes non-homogeneity, avalanche ratio, entropy, floating frequency, frequency distribution, auto-correlation, periodicity, 4-gram pattern analysis.Moreover, four randomness like frequency, serial, run, and poker tests are also added. Finally, a comparative and compact discussion has made on ciphers’ efficiency. This study makes a trade-off, which proves the uniqueness of this work. It opens a new window for the upcoming researchers to search their work area.

Abstract Image

七种经典轻量级密码的统计密码分析
目前,智能世界采用的智能设备与日常生活密不可分。这些智能设备体积小、内存容量低、电池功耗低、计算能力有限,因此重量很轻。传统的加密算法在这些设备上并不适用,这种需求催生了轻量级密码学(LWC)的发展。在各种文献调查中,许多研究人员从面积、吞吐量、延迟、功耗、能量消耗、加密-解密时间等方面分析了轻量级密码。但是,没有一篇论文包含对轻量级密码的各种统计密码分析。这种比特级数据分析可以检查算法在不同攻击下的脆弱性。它确保了密码分析的难度。本文对 PRESENT、SIMON、TEA、SPECK、CLEFIA、MICKEY2.0 和 GRAIN V1 七种经典轻量级密码进行了统计数据分析。分析内容包括非均质性、雪崩比、熵、浮动频率、频率分布、自相关性、周期性、4-gram 模式分析,此外还增加了频率、序列、运行和扑克等四种随机性测试。最后,对密码的效率进行了紧凑的比较讨论。这项研究进行了权衡,证明了这项工作的独特性。它为未来的研究人员打开了一扇寻找工作领域的新窗口。
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
自引率
0.00%
发文量
0
×
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