TY - GEN
T1 - Phishing Web Page Detection Methods
T2 - 2020 IEEE International Conference on Internet of Things and Intelligence Systems, IoTaIS 2020
AU - Faris, Humam
AU - Yazid, Setiadi
N1 - Publisher Copyright:
© 2021 IEEE.
Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.
PY - 2021/1/27
Y1 - 2021/1/27
N2 - 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.
AB - 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.
KW - information security
KW - phishing detection
KW - phishing webpage
KW - URL and HTML features
UR - http://www.scopus.com/inward/record.url?scp=85102187892&partnerID=8YFLogxK
U2 - 10.1109/IoTaIS50849.2021.9359694
DO - 10.1109/IoTaIS50849.2021.9359694
M3 - Conference contribution
AN - SCOPUS:85102187892
T3 - IoTaIS 2020 - Proceedings: 2020 IEEE International Conference on Internet of Things and Intelligence Systems
SP - 167
EP - 171
BT - IoTaIS 2020 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 27 January 2021 through 28 January 2021
ER -