[01078] DNN-based hybrid ensemble learning strategy for XSS detection and defense
Session Time & Room : 2E (Aug.22, 17:40-19:20) @E803
Type : Contributed Talk
Abstract : Due to the high level of intelligence displayed by attackers, existing web-based security applications have failed. When attackers make changes to an organization's data, it is one of the most dangerous attacks (XSS). Combining ML and DL frameworks is proposed as a way to detect and defend against XSS assaults with high accuracy and efficiency. Using this representation, a new method is developed for integrating stacking ensembles into web-based software, which is called "hybrid stacking".