DocumentCode :
3673155
Title :
A hybrid approach to combat email-based cyberstalking
Author :
Zinnar Ghasem;Ingo Frommholz;Carsten Maple
Author_Institution :
IRAC, University of Bedfordshire Luton LU1 3JU, UK
fYear :
2015
fDate :
7/1/2015 12:00:00 AM
Firstpage :
1
Lastpage :
6
Abstract :
Email is one of the most popular Internet applications which enables individuals and organisations alike to communicate and work effectively. However, email has also been used by criminals as a means to commit cybercrimes such as phishing, spamming, cyberbullying and cyberstalking. Cyberstalking is a relatively new surfacing cybercrime, which recently has been recognised as a serious social and worldwide problem. Combating email-based cyberstalking is a challenging task that involves two crucial steps: a robust method for filtering and detecting cyberstalking emails and documenting evidence for identifying cyberstalkers as a prevention and deterrence measure. In this paper, we discuss a hybrid approach that applies machine learning to detect, filter and file evidence. To this end we present a new robust feature selection approach to select informative features, aiming to improve the performance of machine learning within this task.
Keywords :
"Electronic mail","Law enforcement","Computer crime","Feature extraction","Internet","Robustness","Computers"
Publisher :
ieee
Conference_Titel :
Future Generation Communication Technology (FGCT), 2015 Fourth International Conference on
ISSN :
2377-262X
Electronic_ISBN :
2377-2638
Type :
conf
DOI :
10.1109/FGCT.2015.7300257
Filename :
7300257
Link To Document :
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