面向网页篡改检测的混沌MD5算法的研究

Research on Chaotic MD5 Algorithm for Webpage Tampering Detection

随着网页篡改问题的日趋严峻,网页篡改检测技术成为近年来的研究热点。Hash函数校验是目前网页篡改检测任务中常用的一种方法,其中,MD5算法是应用最为广泛的Hash检验函数。然而,在使用MD5算法对网页内容进行校验时,网页内容篡改前后所对应的Hash值存在一定的碰撞问题。针对上述问题,提出了一种面向网页篡改检测的混沌MD5算法,通过基于明文分组的动态参数模型对传统MD5算法的静态参数进行优化,并采用整数帐篷映射对明文分组进行多次迭代,增强算法的抗碰撞性。实验表明,和传统MD5算法相比,混沌MD5算法的Hash值绝对距离与理想值的偏差率减小了0.6047‰,有效降低了网页篡改检测过程中的Hash值碰撞概率。

With the increasing seriousness of webpage tampering problem,webpage tampering detection technology has become a hot research topic in recent years.Hash function verification is a commonly used method in webpage tampering detection tasks.Among them,the MD5 algorithm is the most widely used Hash verification function.However,when the MD5 algorithm is used to verify the webpage content,there is a certain collision problem between the corresponding Hash values before and after the webpage content is tampered with.Aiming at the above problems,this paper proposes a chaotic MD5 algorithm for webpage tampering detection.The static parameters of the traditional MD5 algorithm are optimized through the dynamic parameter model based on plaintext grouping,and the integer tent mapping is used to perform multiple iterations on the plaintext grouping to enhance the collision resistance of the algorithm.Experiments show that,compared with the traditional MD5 algorithm,the deviation rate between the absolute distance of the hash value generated by the chaotic MD5 algorithm and the ideal value is reduced by 0.6047‰,which effectively reduces the collision probability of the hash value in the process of webpage tampering detection.