Machine Learning Techniques for the Detection and Classification of Phishing Emails

Moradpoor, N., Clavie, B., Buchanan, W. (2017). Machine Learning Techniques for the Detection and Classification of Phishing Emails. In: (Ed.) IEEE Technically Sponsored Computing Conference 2017, , () ( ed.). (pp. ). London: . IEEE.


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Abstract

A phishing email is a legitimate-looking email which is designed to fool the recipient into believing that it is a genuine email, and either reveals sensitive information or downloads malicious software through clicking on malicious links contained in the body of the email. Given that phishing emails cost UK consumers £174m in 2015, this paper proposal is driven by a problem whose resolution will have a great impact on people’s lives in the UK and in the world. In this paper, we proposed a Neural Network (NN)-based model for detections and classifications of phishing emails using publically available email datasets for both benign and phishing emails. The results of the experiments are presented in order to demonstrate the effectiveness of the model in terms of accuracy, true-positive rate, false-positive rate, network performance and error histogram.
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Authors

William Buchanan
Director of CDCS
w.buchanan@napier.ac.uk
+44 131 455 2759
Naghmeh Moradpoor
Lecturer in Cybersecurity and Networks
N.Moradpoor@napier.ac.uk
+44 131 455 2596

Areas of Expertise

Cyber-Security
Electronic information now plays a vital role in almost every aspect of our daily lives. So the need for a secure and trustworthy online infrastructure is more important than ever. without it, not only the growth of the internet but our personal interactions and the economy itself could be at risk.

Associated Projects

    Keywords: cyber security