Simplified features for email authorship identification
by Emad E. Abdallah; Alaa E. Abdallah; Mohammad Bsoul; Ahmed F. Otoom; Essam Al-Daoud
International Journal of Security and Networks (IJSN), Vol. 8, No. 2, 2013

Abstract: We present an investigation analysis approach for mining anonymous email content. The core idea behind our approach is concentrated on collecting various effective features from previous emails for all the possible suspects. The extracted features are then used with several machine learning algorithms to extract a unique writing style for each suspect. A sophisticated comparison between the investigated anonymous email and the suspects writing styles is employed to extract evidence of the possible email sender. Extensive experimental results on a real data sets show the improved performance of the proposed method with very limited number of features.

Online publication date: Sun, 18-Aug-2013

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Security and Networks (IJSN):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com