基于拟群串变换的全或无键派生函数

Abdulkadir Hassan Disina, Sapiee Jamel, Z. Pindar, M. M. Deris
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引用次数: 5

摘要

传统的密码学(块和流)使用密钥派生函数(Key Derivation Function, KDF)生成加密密钥。这些kdf通常基于现有的Hash函数和密码作为原语来设计,以实现更好的安全性。然而,这种构造方法对于资源受限的环境来说是昂贵的。kdf的主要功能是生成随机和不可预测的密钥。因此,使用预定义的公共字符串增加了可预测性级别,并向密码分析人员提供了一些密钥的部分知识,从而危及安全性。本文提出了一种新的算法,以最大限度地减少加密哈希函数和密码作为密钥派生函数的使用,并最优地减少KDF中预定义公共字符串的使用。建议的KDF完全依赖于密钥,密码分析师必须正确预测密钥串中的所有元素,否则他将一无所获。为此,将拟群串变换的新定义、基于拟群的可拓函数、键元数据可拓函数和约简函数集成在KDF的设计中。将使用美国国家标准与技术研究院(NIST)开发并推荐的随机性统计测试、Avalanche测试、蛮力测试和相关性评估测试对所提出的算法进行评估。该算法既保证了信息的保密性,又保证了信息的完整性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
All-or-Nothing Key Derivation Function Based on Quasigroup String Transformation
Traditionally, Cryptographic ciphers (Block and Stream) uses Key Derivation Function (KDF) to generate cryptographic keys for encryption purpose. These KDFs are usually designed based on existing Hash functions and ciphers as primitives, to achieve better security. However, this method of construction can be costly to resources- constrain environments. The main function of KDFs is to generate random and unpredictable secret keys. Therefore, the use of predefined public string increases the predictability level and provides some partial knowledge of the key to cryptanalyst, thus jeopardies the security. This paper proposed a new algorithm to minimize the use of cryptographic Hash function and ciphers as a key derivation function and to optimally mitigate the use of predefined public string in KDF. The proposed KDF is entirely key-dependent and cryptanalyst has to correctly predict all the elements in the key string otherwise he got nothing. To achieve that, a new definition of Quasigroup string transformation, a Quasigroup- based expansion function, and key-metadata expansion function as well as reduction function are integrated together in the design of the proposed KDF. The proposed algorithm will be evaluated using statistical test for Randomness developed and recommended by the National Institute of Standard and Technology (NIST), Avalanche, Brute Force and Correlation Assessment test. The proposed algorithm will ensure not only confidentiality of information but integrity as well.
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