Paper Info
Title
An anti-phishing enterprise environ model using feed-forward backpropagation and Levenberg-Marquardt method
Abstract
Phishing in an enterprise is serious issue rising in wide scale and complexity, as phishers use email phishing via obfuscated, malicious or phished URLs and continuously adapt or innovate their strategies to lure victims for identity theft for financial benefits. To gain victim's trust and confidence phishers have started using visceral factors and familiarity cues. Phishing is not always money centric; phisher defame the user's goodwill and character. Defamation in enterprise could be much more traumatic than being embarrassed at a social networking site. It is a challenging task to address this issue. It is evident through literature review that single phishing detection filter approaches are insufficient to detect phishing in enterprise environ. Therefore, a novel anti-phishing model for enterprise using artificial neural network is proposed. In addition, this model effectively identifies whether the phishing email is known phishing or unknown phishing to reduce the trust and familiarity-based email phishing enterprise environ. The feed-forward backpropagation and Levenberg-Marquart methods of ANN are adopted to enhance the URL classification process and with Fuzzy Inference System to get result with imprecise data of social features. The proposed model can accurately classify the known and unknown email phishing via URLs.
Year
DOI
Venue
2021
10.1002/spy2.132
SECURITY AND PRIVACY
Keywords
DocType
Volume
authentication, E-mail phishing, enterprise cyber threat, machine learning techniques, privacy models for communication systems communication security, security and privacy in mobile communication services, social engineering
Journal
4
Issue
ISSN
Citations 
1
2475-6725
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Shweta Sankhwar122.04
Dhirendra Pandey200.34
Raees Ahmad Khan300.34
Sachi Nandan Mohanty400.68