信息安全的智能系统
Intelligent Systems for Information Security
摘要：
本论文的目的是利用智能系统来扩展和提高密码技术的性能和安全性。提出了一种求解密码分析问题的遗传算法框架。提出了一种新的基于遗传算法的差分密码分析方法，并提出了一种基于被攻击密码差分特征的适应度测度。通过对基本的置换置换网络和Feistel网络进行攻击，证明了该攻击的复杂度小于对同一密码进行差分分析的复杂度的四分之一。用现代分组密码的基本模型代替实际密码进行攻击，证明该攻击也适用于其他易受差分分析攻击的密码。基于神经网络的映射逼近能力，提出了一种新的分组密码攻击方法。一个完整的问题制定的解释和实施的攻击，一些假设的Feistel密码不容易受到差分或线性攻击。提出了一种基于神经网络的分组密码算法。给出了一个完整的密码结构和密钥调度。神经网络的主要特性是能够在一个非常快速和非常小的存储器相比，S-盒执行大的维度域之间的映射被用作密码的基础。
英文摘要：
This thesis aims to use intelligent systems to extend and improve performance and security of cryptographic techniques. Genetic algorithms framework for cryptanalysis problem is addressed. A novel extension to the differential cryptanalysis using genetic algorithm is proposed and a fitness measure based on the differential characteristics of the cipher being attacked is also proposed. The complexity of the proposed attack is shown to be less than quarter of normal differential cryptanalysis of the same cipher by applying the proposed attack to both the basic Substitution Permutation Network and the Feistel Network. The basic models of modern block ciphers are attacked instead of actual cipher to prove that the attack is applicable to other ciphers vulnerable to differential cryptanalysis. A new attack for block cipher based on the ability of neural networks to perform an approximation of mapping is proposed. A complete problem formulation is explained and implementation of the attack on some hypothetical Feistel cipher not vulnerable to differential or linear attacks is presented. A new block cipher based on the neural networks is proposed. A complete cipher structure is given and a key scheduling is also shown. The main properties of neural network being able to perform mapping between large dimension domains in a very fast and a very small memory compared to S-Boxes is used as a base for the cipher.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
