WEB BROWSER EXTENSION FOR DETECTING COVID-19 THEMED MALICIOUS WEB CONTENT
| dc.contributor.author | BELOUADAH et SALEM, KHALIL et MOHAMED EL-AMINE | |
| dc.date.accessioned | 2021-07-12T14:45:28Z | |
| dc.date.available | 2021-07-12T14:45:28Z | |
| dc.date.issued | 2021 | |
| dc.description.abstract | In light of the spread of the Covid-19 virus and the necessity of using the Internet as remote work, malicious content on the web has become a global threat to web users, as its huge spread has made users vulnerable to all kinds of cyber-attacks that can be carried out behind websites. Several recent researches have been proposed to detect harmful content on the subject of COVID-19, however detection of COVID-19 themed malicious websites has not been entirely resolved until now. In this work, we propose a chrome extension to detect malicious web content with the theme of COVID-19 by analyzing HTTP requests and responses. The extension relies on a list of malicious features built with a machine learning classifier, and it does more protection. The experimental results obtained demonstrate the effectiveness of our extension in detecting malicious content with the theme of COVID-19, which was demonstrated by the perfect accuracy score. | en_US |
| dc.identifier.uri | https://repository.univ-msila.dz/handle/123456789/24894 | |
| dc.language.iso | en | en_US |
| dc.publisher | FACULTY: MATHIMATICS AND COMPUTER SCIENCE DEPARTEMENT: COMPUTER SCIENCE - OPTION: RTIC | en_US |
| dc.subject | COVID-19, Malicious Websites, Web Browser Extension, Detection, Machine learning. | en_US |
| dc.title | WEB BROWSER EXTENSION FOR DETECTING COVID-19 THEMED MALICIOUS WEB CONTENT | en_US |
| dc.type | Thesis | en_US |