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Profiling phishing email based on clustering approach
In this paper, an approach for profiling email-born phishing activities is proposed. Profiling phishing activities are useful in determining the activity of an individual or a particular group of phishers. By generating profiles, phishing activities can be well understood and observed. Typically, work in the area of phishing is intended at detection of phishing emails, whereas we concentrate on profiling the phishing email. We formulate the profiling problem as a clustering problem using the various features in the phishing emails as feature vectors. Further, we generate profiles based on clustering predictions. These predictions are further utilized to generate complete profiles of these emails. The performance of the clustering algorithms at the earlier stage is crucial for the effectiveness of this model. We carried out an experimental evaluation to determine the performance of many classification algorithms by incorporating clustering approach in our model. Our proposed profiling email-born phishing algorithm (ProEP) demonstrates promising results with the RatioSize rules for selecting the optimal number of clusters.
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Event
IEEE Trust, Security and Privacy in Computing and Communications. Conference (12th : 2013 : Melbourne, Vic)Pagination
628 - 635Publisher
IEEE Computer SocietyLocation
Melbourne, VicPlace of publication
Piscataway, N.J.Publisher DOI
Start date
2013-07-16End date
2013-07-18ISBN-13
9780769550220Language
engPublication classification
E1 Full written paper - refereed; E Conference publicationCopyright notice
2013, IEEETitle of proceedings
TrustCom 2013 : Proceedings of the 12th IEEE International Conference on Trust, Security and Privacy in Computing and CommunicationsUsage metrics
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