TY  - CONF
KW  - Classification (of information); Computer crime; Data mining; Losses; Machine learning; Surveys
KW  -  Attack detection; Attack methods; Email Detection; Email filtering; Financial loss; Phishing; Phishing attacks; Phishing email; Service provider; Technology attack
KW  -  Electronic mail
N1  - cited By 4; Conference of 4th International Conference on Innovative Computing, ICIC 2021 ; Conference Date: 9 November 2021 Through 10 November 2021; Conference Code:176892
TI  - A Survey on Phishing Emails Detection Techniques
SN  - 9781665400916
ID  - scholars15355
A1  - Muneer, A.
A1  - Ali, R.F.
A1  - Al-Sharai, A.A.
A1  - Fati, S.M.
Y1  - 2021///
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85126691220&doi=10.1109%2fICIC53490.2021.9692960&partnerID=40&md5=03c52c67926577fa64826435f681b68f
AV  - none
PB  - Institute of Electrical and Electronics Engineers Inc.
N2  - In the last few eras, phishing attacks have become more sensitive case for local users, organizations, and service providers. Phishing emails can also cause financial loss to organizations and individuals. Phishing attackers swindle the user or organization's information by sending them fake emails that resemble most of their work. Many researchers proposed different methods to avoid phishing emails, but this problem has not been fully solved. Over time, there is a rapid increase in technology and phishing attack methods and detection techniques. The network users want the complete solution to avoid phishing attacks, which is quite difficult; however, using many methods can avoid phishing emails. In this survey paper, we present an overview of the state-of-the-art techniques to detect phishing emails. We perform a comprehensive study of these techniques and evaluate them. This provides an understanding of the problem; its solution space and future research directions are also proposed. © 2021 IEEE.
ER  -