Optimizéd XSS Vulnerability Scanner Approach
| dc.contributor.author | BOULANOUAR, SOUHIL LARBI | |
| dc.contributor.author | Supervisor: SAOUDI, LALIA | |
| dc.date.accessioned | 2023-05-31T08:36:27Z | |
| dc.date.available | 2023-05-31T08:36:27Z | |
| dc.date.issued | 2016-06-10 | |
| dc.description.abstract | The Web applications are becoming more popular with the advancement of technology. However, the web security is becoming one of the most common security issues. This report focuses on the XSS vulnerabilities which commonly present in most Web applications and can create serious security problems. In our work, we propose a black box detection approach using optimal attack vector. This method generates an attack vector automatically, optimizes the attack vector repertory using a mutation operator model, and detects XSS vulnerabilities in web applications dynamically. | en_US |
| dc.identifier.uri | http://dspace.univ-msila.dz:8080//xmlui/handle/123456789/39057 | |
| dc.language.iso | en | en_US |
| dc.publisher | University of M'sila | en_US |
| dc.subject | XSS vulnerability detection, attack vector optimization, black box scanner, XSS vulnerability scanner. | en_US |
| dc.title | Optimizéd XSS Vulnerability Scanner Approach | en_US |
| dc.type | Thesis | en_US |