dc.contributor.author | Yasmin, Sabina | |
dc.contributor.author | Roy, Mou | |
dc.date.accessioned | 2020-11-29T04:24:05Z | |
dc.date.available | 2020-11-29T04:24:05Z | |
dc.date.issued | 2020-10-01 | |
dc.identifier.uri | http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/5206 | |
dc.description.abstract | Phishing is one of the top most cybercrime according to a lot cybercrime awareness organization. “Exploratory data analysis of phishing sites to identify most important features to detect a phishing site" is a research project which aims to explore the most significant features of a phishing site in order to detect a phishing site. In order to explore these features data were collected from an open source machine learning data repository. Later correlation and univariate selection methods were applied to discover the most significant features to detect a phishing site. Finally, based on the top five selected features a system was built to check whether it can identity phishing sites or not. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Daffodil International University | en_US |
dc.subject | Phishing | en_US |
dc.subject | Cyberterrorism | en_US |
dc.subject | Espionage | en_US |
dc.title | Exploratory Data Analysis of Phishing Sites to Identify Most Important Features to Detect a Phishing Site | en_US |
dc.type | Other | en_US |