Detecting phishing emails using hybrid features
- Authors: Ma, Liping , Ofoghi, Bahadorreza , Watters, Paul , Brown, Simon
- Date: 2009
- Type: Text , Conference paper
- Relation: Paper presented at 2009 Symposia and Workshops on Ubiquitous, Autonomic and Trusted Computing, UIC-ATC '09, Brisbane, Queensland : 7th-9th July 2009 p. 493-497
- Full Text:
- Description: Phishing emails have been used widely in fraud of financial organizations and customers. Phishing email detection has drawn a lot attention for many researchers and malicious detection devices are installed in email servers. However, phishing has become more and more complicated and sophisticated and attack can bypass the filter set by anti-phishing techniques. In this paper, we present a method to build a robust classifier to detect phishing emails using hybrid features and to select features using information gain. We experiment on 10 cross-validations to build an initial classifier which performs well. The experiment also analyses the quality of each feature using information gain and best feature set is selected after a recursive learning process. Experimental result shows the selected features perform as well as the original features. Finally, we test five machine learning algorithms and compare the performance of each. The result shows that decision tree builds the best classifier.
- Description: 2003007857
The impact of semantic class identification and semantic role labeling on natural language answer extraction
- Authors: Ofoghi, Bahadorreza , Yearwood, John , Ma, Liping
- Date: 2008
- Type: Text , Conference paper
- Relation: Paper presented at 30th European Conference on IR Research, ECIR 2008, Glasgow, UK : 30th March - 3rd April 2008 p. 430-437
- Full Text: false
- Description: In satisfying an information need by a Question Answering (QA) system, there are text understanding approaches which can enhance the performance of final answer extraction. Exploiting the FrameNet lexical resource in this process inspires analysis of the levels of semantic representation in the automated practice where the task of semantic class and role labeling takes place. In this paper, we analyze the impact of different levels of semantic parsing on answer extraction with respect to the individual sub-tasks of frame evocation and frame element assignment.
- Description: 2003006587
FrameNet-based fact-seeking answer processing : A study of semantic alignment techniques and lexical coverage
- Authors: Ofoghi, Bahadorreza , Yearwood, John , Ma, Liping
- Date: 2008
- Type: Text , Journal article
- Relation: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 5360 LNAI, no. (1 December 2008 through 5 December 2008 2008), p. 192-201
- Full Text: false
- Description: In this paper, we consider two aspects which affect the performance of factoid FrameNet-based Question Answering (QA): i) the frame semantic-based answer processing technique based on frame semantic alignment between questions and passages to identify answer candidates and score them, and ii) the lexical coverage of FrameNet over the predicates which represent the main actions in question and passage events. These are studied using a frame semantic-based QA run over the TREC 2004 and TREC 2006 factoid question sets. © 2008 Springer Berlin Heidelberg.
Two-step comprehensive open domain text annotation with frame semantics
- Authors: Ofoghi, Bahadorreza , Yearwood, John , Ma, Liping
- Date: 2007
- Type: Text , Conference paper
- Relation: Paper presented at Australasian Language Technology Workshop 2007, Melbourne Zoo, Melbourne, Victoria : 10th-11th December 2007 p. 83-91
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- Description: With shallow semantic parsing tasks receiving more attention in many natural language applications, there is a need for labelled corpora for learning the specific tags under consideration. In this paper, we discuss a two-step semantic class and semantic role assignment based on the FrameNet elements over a subset of the AQUAINT collection with a reasonable coverage over the semantic frames in FrameNet. The quality of the annotation task is examined through inter-annotator agreement. The methodology described in this work for measuring inter-annotator agreement can be adapted for similar tasks. Some central aspects of the task are also detailed in this paper.
- Description: 2003005522
Automatic sleep stage identification: difficulties and possible solutions
- Authors: Sukhorukova, Nadezda , Stranieri, Andrew , Ofoghi, Bahadorreza , Vamplew, Peter , Saleem, Muhammad Saad , Ma, Liping , Ugon, Adrien , Ugon, Julien , Muecke, Nial , Amiel, Hélène , Philippe, Carole , Bani-Mustafa, Ahmed , Huda, Shamsul , Bertoli, Marcello , Levy, P , Ganascia, J.G
- Date: 2010
- Type: Text , Conference proceedings
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- Description: The diagnosis of many sleep disorders is a labour intensive task that involves the specialised interpretation of numerous signals including brain wave, breath and heart rate captured in overnight polysomnogram sessions. The automation of diagnoses is challenging for data mining algorithms because the data sets are extremely large and noisy, the signals are complex and specialist's analyses vary. This work reports on the adaptation of approaches from four fields; neural networks, mathematical optimisation, financial forecasting and frequency domain analysis to the problem of automatically determing a patient's stage of sleep. Results, though preliminary, are promising and indicate that combined approaches may prove more fruitful than the reliance on a approach.
Applying clustering and ensemble clustering approaches to phishing profiling
- Authors: Webb, Dean , Yearwood, John , Vamplew, Peter , Ma, Liping , Ofoghi, Bahadorreza , Kelarev, Andrei
- Date: 2009
- Type: Text , Conference paper
- Relation: Paper presented at Eighth Australasian Data Mining Conference, AusDM 2009, University of Melbourne, Melbourne, Victoria : 1st–4th December 2009
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- Description: 2003007911