Grain-128密码系统识别研究

Zhicheng Zhao, Yaqun Zhao, Fengmei Liu
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引用次数: 0

摘要

密码系统识别是识别攻击的一个重要方面,是密码分析的基础。我们主要研究了在其他11种密码系统之间对Grain-128的识别。首先提取密文的25个特征,然后构建基于随机森林算法的密码识别分类器。实现了Grain-128与其他11种密码系统的识别实验。实验结果表明,在已知密文的情况下,Grain-128可以有效地从其他11种密码系统中识别出来,基于随机性测试的特征的性能优于其他现有特征,其密码系统识别准确率平均在10%以上。在保持特征性能的前提下,t-SNE算法完成了部分特征的降维,提高了特征的数据效用。Keywords-cryptosystem识别;块密码;随机性测试;特征提取;随机森林
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on Grain-128's cryptosystem recognition
As an important aspect of distinguishing attack, cryptosystem recognition is the foundation of cryptanalysis. We mainly focused on the recognition of Grain-128 between other 11 cryptosystems. Firstly, we extracted 25 features of ciphertexts, then we constructed cryptosystem recognition classifier based on random forest algorithm. The recognition experiments between Grain-128 and other 11 cryptosystems were implemented. The results of experiments show that, in the condition of known ciphertext, Grain-128 can be effectively identified from other 11 cryptosystems, the performance of randomness test based features are better than other existed features with its accuracy of cryptosystem recognition average over 10%. With maintaining the performance of features, some features’ dimension reductions are completed and features’ data utilities are improved by t-SNE algorithm. Keywords—cryptosystem recognition; block cipher; randomness test; feature extraction; random forest
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