A hybrid approach to combat email-based cyberstalking

Zinnar Ghasem
,
Ingo Frommholz
,
Carsten Maple

University of Bedfordshire
,
University of Warwick

Research Output: Chapter in Book/Report/Conference proceeding Conference contribution Peer-review

Sustainable Development Goals

SDG 16 Peace, Justice and Strong Institutions

Abstract

Email is one of the most popular Internet ap- plications 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.

Publication Information

Output type

Research Output: Chapter in Book/Report/Conference proceeding Conference contribution Peer-review

Original language

English

Publication milestones

Published - 26/10/2015

Publication status

Published - 26/10/2015

Publisher

Institute of Electrical and Electronics Engineers Inc., United States

ISBN (Print)

9781479982660

External Publication IDs

handle.net: 10547/624259
Scopus: 84963579156

Host publication title

2015 Fourth International Conference on Future Generation Communication Technology (FGCT)

Access to documents

10.1109/FGCT.2015.7300257

Publication metrics

Metrics

Scopus