Email Spoofing Attack Detection through an End to End Authorship Attribution System

Giacomo Giorgi, Andrea Saracino, Fabio Martinelli

Abstract

This paper proposes a novel email author verification aimed at tackling email spoofing attacks. The proposed approach exploits an authorship technique based on the analysis of the author’s writing style. The problem has been studied under two viewpoints, i.e. the typical sender verification viewpoint, already exploited in previous works, and the sender-receiver interaction verification, which to the best of our knowledge is a novel approach. Hence, we introduced the concept of end-to-end email authorship verification, which is focused on the analysis of the sender-receiver interactions. The proposed method implements a binary classification exploiting both standard machine learning classifiers based on the well-known text stylometric features and deep learning classifiers based on the automatic feature extraction phase. We have used a well-known email dataset, i.e. the Enron dataset to benchmark our approach, with the experiments showing an authorship verification accuracy reaching 99% and 93% respectively for the sender and the end to end verification scenarios. The proposed method has been implemented as an end-user support system in the Android environment for email spoofing attack detection.

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Paper Citation


in Harvard Style

Giorgi G., Saracino A. and Martinelli F. (2020). Email Spoofing Attack Detection through an End to End Authorship Attribution System.In Proceedings of the 6th International Conference on Information Systems Security and Privacy - Volume 1: ICISSP, ISBN 978-989-758-399-5, pages 64-74. DOI: 10.5220/0008954600640074


in Bibtex Style

@conference{icissp20,
author={Giacomo Giorgi and Andrea Saracino and Fabio Martinelli},
title={Email Spoofing Attack Detection through an End to End Authorship Attribution System},
booktitle={Proceedings of the 6th International Conference on Information Systems Security and Privacy - Volume 1: ICISSP,},
year={2020},
pages={64-74},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008954600640074},
isbn={978-989-758-399-5},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 6th International Conference on Information Systems Security and Privacy - Volume 1: ICISSP,
TI - Email Spoofing Attack Detection through an End to End Authorship Attribution System
SN - 978-989-758-399-5
AU - Giorgi G.
AU - Saracino A.
AU - Martinelli F.
PY - 2020
SP - 64
EP - 74
DO - 10.5220/0008954600640074