Tamper Detection of Batch Websites Based on Text Comparison

Currently, information search on websites is an indispensable part of daily life. It is an important platform to obtain resources, such as regular notifications or current affairs about relevant companies, schools or other organizations. However, websites are prone to tampering by malicious attacks and thus tamper detection for websites is an important countermeasure to maintain the credibility and integrity of information found on websites. In this paper, we propose a highly feasible batch website tamper detection method based on text comparison. Different algorithms for text comparison have been proposed to analyze various websites with with varying degrees tamper detection using three factors: time efficiency, accuracy of detection and memory consumption. The experiments demonstrated that different algorithms have varying performances in terms of website tamper detection but nevertheless the string comparison method has more advantages under normal circumstances.