Design And Analysis Of Hash Functions Based On Integer Chaos

In the Internet era,the chemical industrial control system faces the risk of network attacks,and the authentication technology must be used to improve the security of the chemical industrial control system,and the Hash function can be a solution because of its one-way nature and fixed output length.The Hash function plays an indispensable role in the process of securing information.The key to judge the superior performance of Hash function is whether it has good sensitivity and good chaos and diffusion characteristics.Chaotic systems are often used in the design of Hash functions because of their natural initial value sensitivity and internal randomness.In this paper,firstly combine the one-dimensional bi-directional coupled image lattice model and dynamic integer tent mapping to construct a parallel Hash function using Merkle tree structure;then we extend the one-dimensional coupled lattice mapping to two dimensions and add dynamic parameters to the process of model coupling to construct a more secure Hash function;on this basis,we combine the Spark big data platform to design a more secure and efficient Hash function.Based on this,a more secure and efficient Hash function is designed in combination with Spark big data platform.The main research contents are.(1)Analyze the iteration of the tent mapping,convert it from real domain operation to integer domain operation,and add dynamic parameters to significantly improve the cryptographic properties of the chaotic mapping.For the problem of slow running of chaotic Hash function,a new parallel Hash function is designed by using Merkle tree structure and combining the chaos and diffusion mechanism of the one-dimensional two-way coupled image lattice model.Theoretical analysis and test results show that the Hash function has a more desirable initial value sensitivity and chaos and diffusion properties,and can complete the hash processing of data in a shorter time,and can obtain different lengths of Hash values as needed,meeting the performance requirements of the Hash function.(2)The one-dimensional two-way coupled image lattice model is extended to a two-dimensional structure,and the Hash function is constructed by combining dynamic integer tent mapping.The bit-logic determination function of dynamic integer tent mapping is used to control the change of dynamic parameters,and the dynamic parameters are evolved by circular displacement method,which enhances the correlation between explicit difference and parameter terms.The extension of dimensionality with the inclusion of dynamic parameter terms and their evolution mechanism makes the model enhanced not only in terms of diffusion speed but also in terms of confusion and diffusion properties.Theoretical analysis and various test results show that the algorithm has strong initial value sensitivity,significantly improved chaos and diffusion efficiency,and simple implementation.(3)A Hash function for Spark big data platform is designed to address the problems of poor security and low efficiency of the Hash function when dealing with large data volume of plaintext information.The plaintext is read and sliced in Spark big data platform,and then each data block is processed in parallel;the Merkle tree structure is used to compress the data by taking fixed length data at a time,and the compression function adopts a two-dimensional coupled image lattice with dynamic integer tent mapping,and additional dynamic parameters are added to enhance the obfuscation performance.The theoretical analysis and various test results show that the algorithm has good initial value sensitivity and parallel processing characteristics,providing an efficient and fast solution for applications such as authentication and digital signature of large data volume plaintext information.