Phishing Detection Using PSOAANN Based One-Class Classifier

Author

Pandey, Manjusha ; Ravi, Vignesh

Author_Institution

Inst. for Dev. & Res. in Banking Technol., Hyderabad, India

fYear

2013

fDate

16-18 Dec. 2013

Firstpage

148

Lastpage

153

Abstract

We propose to detect phishing emails and websites using particle swarm optimization (PSO) trained auto associative neural network (PSOAANN), which is employed as one class classifier. PSOAANN achieved better results when compared to previous efforts. In the study, we also developed a new feature selection method based on the weights from input to hidden layers of the PSOAANN. We compared its performance with other methods.

Keywords

computer crime; feature selection; neural nets; particle swarm optimisation; pattern classification; unsolicited e-mail; PSOAANN based one-class classifier; feature selection method; particle swarm optimization trained auto associative neural network; phishing Websites; phishing detection; phishing emails; Accuracy; Electronic mail; Feature extraction; Input variables; Neural networks; Sensitivity; Training; feature selection; one class classifier; particle swarm optimization; phishing detection;

fLanguage

English

Publisher

ieee

Conference_Titel

Emerging Trends in Engineering and Technology (ICETET), 2013 6th International Conference on

Conference_Location

Nagpur

Print_ISBN

978-1-4799-2560-5

Type

conf

DOI

10.1109/ICETET.2013.46

Filename

6754808

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3451495