TWC: Small: Design and Analysis of Symmetric Key Ciphers

伪随机序列具有统计随机性，被广泛应用于需要随机性并且可以有效地生成伪随机序列的应用中。数字计算和通信中的许多日常应用都需要随机性才能正确运行。例如，这些包括安全网络通信、全球定位系统，甚至天气预报模拟。然而，目前已知的高质量伪随机序列的通用生成器很少。这项研究将开发算法和软件工具来制作高质量的可用的伪随机序列，特别是将导致在性能和安全性方面比现有的对称密钥密码更好的改进。这个项目涉及高速数据加密机制的设计：Feistel网络，一个广泛使用的分组密码体系结构；布尔函数，用于分组密码和流密码的构建块；以及带进位移位寄存器(FCSR)和泛化(AFSR)，具有许多理想特性的序列生成器。FCSR的许多基本性质已经被确定，并已被用于流密码和准蒙特卡罗。我们建议(1)利用新的类Feistel网络或使用伪随机序列发生器来开发新的分组密码设计；(2)用FCSR代替LFSR来研究流密码；(3)研究布尔函数的随机性；(4)进一步分析AFSR，例如解决更一般AFSR的寄存器合成问题；以及(5)开发高效的序列发生器的实现。

Pseudorandom sequences (PRS) exhibit a statistical randomness and are widely used in applications where randomness is needed and PRS generation can be effectively done. Many everyday applications in digital computing and communication require randomness to operate correctly. For example, these include secure network communications, global positioning systems, and even weather prediction simulations. Yet, few general generators of high quality pseudorandom sequences are known. This research will develop algorithms and software tools to make high quality usable pseudorandom sequences, particularly, which would lead to improvements in performance and security over current symmetric key ciphers. This project concerns the design of high speed mechanisms for data encryption: Feistel networks, a widely used architecture for block ciphers; Boolean functions, building blocks for both block ciphers and stream ciphers; and feedback-with-carry shift registers (FCSRs) and generalizations (AFSRs), generators of sequences with many desirable properties. Many basic properties of FCSRs have been determined and they have been used in stream ciphers and quasi-Monte Carlo. We propose to (1) develop new designs of block ciphers with new Feistel-like networks or time varying keys using PRS generators; (2) study stream ciphers with FCSRs replacing LFSRs; (3) study measures of randomness of Boolean functions; (4) further analyze AFSRs, e.g. solve the register synthesis problem for more general AFSRs; and (5) develop efficient implementations of sequence generators.