Comparison of XSS vulnerability detection techniques in free email service messaging

Abstract

In this quantitative research work, it has been proposed as an objective to implement the best XSS vulnerability detection comparison technique in free mail services messaging. Email serves us for the communication of sending and receiving messages quickly and easily can be to one or thousands of people, with attached content of files, images or other documents, this valuable information is being very sensitive and attacked by cyber hackers looking for a weakness where to enter, can be from the uniform resource locator URL Database, misleading advertising, cloning of web pages, messages with viruses and that during network traffic that malicious people who are in the expectation of an oversight to be able to infiltrate and steal confidential information, every day are more sophisticated causing damage in monetary matters. The XSS e-mail repository is divided into two parts, the first being the classification of good and bad e-mails. In the construction of the database was used a repository of emails https://www.kaggle.com, a number considered has been 1000 emails to perform automatic classification in the segmentation part was implemented for training automatic classification of support machine (SVM) is used vectors characteristics resulting in accuracy, accuracy, sensitivity and specificity. The results obtained gave an accuracy of 100% which suggests that SVM can be used for vulnerability detection in emails.