- Title
- Establishing phishing provenance using orthographic features
- Creator
- Liping, Ma; Yearwood, John; Watters, Paul
- Date
- 2009
- Type
- Text; Conference paper
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/43550
- Identifier
- vital:3667
- Identifier
-
https://doi.org/10.1109/ECRIME.2009.5342604
- Identifier
- ISBN:9781424446254
- Abstract
- After phishing message detection, determining the provenance of phishing messages and Websites is the second step to tracing cybercriminals. In this paper, we present a novel method to cluster phishing emails automatically using orthographic features. In particular, we develop an algorithm to cluster documents and remove redundant features at the same time. After collecting all the possible features based on observation, we adapt the modified global k-mean method repeatedly, and generate the objective function values over a range of tolerance values across different subsets of features. Finally, we identify the appropriate clusters based on studying the distribution of the objective function values. Experimental evaluation of a large number of computations demonstrates that our clustering and feature selection techniques are highly effective and achieve reliable results.
- Publisher
- Tacoma, Washington : IEEE
- Relation
- Paper presented at 2009 eCrime Researchers Summit, eCRIME '09, Tacoma, Washington : 20th-21st October 2009
- Rights
- Copyright IEEE
- Rights
- Open Access
- Rights
- This metadata is freely available under a CCO license
- Subject
- Clustering; Feature elimination; Feature selection; Modified global k-means
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