论文标题
部分可观测时空混沌系统的无模型预测
Matrix Based Adaptive Short Block Cipher
论文作者
论文摘要
每天，数百万个信用卡都会刷卡，并在世界范围内进行交易。由于多种形式的不道德数字活动，用户容易受到信用卡欺诈，网络钓鱼，身份盗用等的影响。本文概述了一种新颖的块加密算法，该算法涉及多个私钥和弹性的Trapdoor功能，可确保数据安全性，同时保持最佳的运行时间和空间的复杂性。所提出的方案由基于抑郁的立方函数和独特的密钥生成算法的不可抑制的板门组成，该算法使用斐波那契序列和可逆的方形矩阵来提高安全性。该论文涉及从综合的密码分析中获得的数据，从而利用了系统的优势和劣势，并评论了其潜在的大规模行业应用。
Every day, millions of credit cards are swiped and transactions are carried out across the world. Due to numerous forms of unethical digital activities, users are vulnerable to credit card fraud, phishing, identity theft, etc. This paper outlines a novel block encryption algorithm involving multiple private keys and a resilient trapdoor function that ensures data security while maintaining an optimal run time and space complexity. The proposed scheme consists of an irrepressible trapdoor based on a depressed cubic function and a unique key generation algorithm that uses Fibonacci sequences and invertible square matrices for improved security. The paper involves data obtained from comprehensive cryptanalysis exploiting the strengths and weaknesses of the system and comments on its potential large-scale industry applications.
