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  4. Recognizing Email Spam from Meta Data Only
 
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2019
Conference Paper
Title

Recognizing Email Spam from Meta Data Only

Abstract
We propose a new spam detection approach based solely on meta data features gained from email headers. The approach achieves above 99 % classification accuracy on the CSDMC2010 dataset, which matches or surpasses state-of-the-art spam classifiers. We utilize a static set of engineered features, supplemented with automatically extracted features. The approach is just as effective for spam detection in end-to-end encryption, as our feature set remains unchanged for encrypted emails. In contrast to most established spam detectors, we disregard the email body completely and can therefore deliver very high classification speeds, as computationally expensive text preprocessing is not necessary.
Author(s)
Krause, Tim  
Uetz, Rafael  
Kretschmann, Tim
Mainwork
IEEE Conference on Communications and Network Security, CNS 2019  
Conference
Conference on Communications and Network Security (CNS) 2019  
DOI
10.1109/CNS.2019.8802827
Language
English
Fraunhofer-Institut für Kommunikation, Informationsverarbeitung und Ergonomie FKIE  
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