| Title | Phishing Web Page Detection Methods: URL and HTML Features Detection |
| Publication Type | Conference Paper |
| Year of Publication | 2021 |
| Authors | Faris, Humam, Yazid, Setiadi |
| Conference Name | 2020 IEEE International Conference on Internet of Things and Intelligence System (IoTaIS) |
| Date Published | jan |
| Keywords | feature extraction, Human Behavior, Information security, machine learning, phishing, Phishing Detection, phishing webpage, pubcrawl, Syntactics, Training data, Uniform resource locators, URL and HTML features, Web pages |
| Abstract | Phishing is a type of fraud on the Internet in the form of fake web pages that mimic the original web pages to trick users into sending sensitive information to phisher. The statistics presented by APWG and Phistank show that the number of phishing websites from 2015 to 2020 tends to increase continuously. To overcome this problem, several studies have been carried out including detecting phishing web pages using various features of web pages with various methods. Unfortunately, the use of several methods is not really effective because the design and evaluation are only too focused on the achievement of detection accuracy in research, but evaluation does not represent application in the real world. Whereas a security detection device should require effectiveness, good performance, and deployable. In this study the authors evaluated several methods and proposed rules-based applications that can detect phishing more efficiently. |
| DOI | 10.1109/IoTaIS50849.2021.9359694 |
| Citation Key | faris_phishing_2021 |
Phishing Web Page Detection Methods: URL and HTML Features Detection