Classification of Web History Tools Through Web Analysis

Abstract

Web pages may contain various types of sensitive information exposed, such as user login information. Even after these pages have been corrected, the sensitive information, once exposed, can be found through the web history tools. These tools make snapshots of web pages, that is, capture the state of the pages in the most varied periods. Although these tools are widely used, it is not known which web history tool is the most accessed. A method to find out which web history tool is the most accessed is by means of classification using the web analytics technique. Therefore, in view of this scenario, the objective of this work was to classify web history tools through web analysis. The methodology used was the descriptive with quantitative approach. As for the technical procedures, this work is characterized as experimental to verify if the technique of web analysis is able to classify web history tools. The results show that the technique of web analysis produces indicators capable of classifying the web history tools by the total number of accesses received.