| Title | Detecting Exploit Websites Using Browser-based Predictive Analytics |
| Publication Type | Conference Paper |
| Year of Publication | 2019 |
| Authors | Almousa, May, Anwar, Mohd |
| Conference Name | 2019 17th International Conference on Privacy, Security and Trust (PST) |
| Keywords | browser-based predictive analytics, composability, compositionality, cyberattacks, cybersecurity, data analytics, data privacy, Human Behavior, human computer interaction, human factors, Information analysis, learning (artificial intelligence), machine learning, machine learning-powered predictive analytical model, Metrics, predictive analytics, pubcrawl, resilience, Resiliency, threat detection, tool development, Web browser, Web Browser Security, web browser vulnerabilities, Web browsers, Web sites, Web-based computing |
| Abstract | The popularity of Web-based computing has given increase to browser-based cyberattacks. These cyberattacks use websites that exploit various web browser vulnerabilities. To help regular users avoid exploit websites and engage in safe online activities, we propose a methodology of building a machine learning-powered predictive analytical model that will measure the risk of attacks and privacy breaches associated with visiting different websites and performing online activities using web browsers. The model will learn risk levels from historical data and metadata scraped from web browsers. |
| DOI | 10.1109/PST47121.2019.8949037 |
| Citation Key | almousa_detecting_2019 |
Detecting Exploit Websites Using Browser-based Predictive Analytics