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Robert Layton
Robert Layton
Federation University Australia
Verified email at datapipeline.com.au - Homepage
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Cited by
Year
API design for machine learning software: experiences from the scikit-learn project
L Buitinck, G Louppe, M Blondel, F Pedregosa, A Mueller, O Grisel, ...
arXiv preprint arXiv:1309.0238, 2013
19572013
Authorship attribution for twitter in 140 characters or less
R Layton, P Watters, R Dazeley
Cybercrime and Trustworthy Computing Workshop (CTC), 2010 Second, 1-8, 2010
1732010
Malware Detection Based on Structural and Behavioural Features of API Calls
M Alazab, R Layton, S Venkataraman, P Watters
School of Computer and Information Science, Security Research Centre, Edith …, 2010
852010
A methodology for estimating the tangible cost of data breaches
R Layton, PA Watters
Journal of Information Security and Applications 19 (6), 321-330, 2014
722014
Automated unsupervised authorship analysis using evidence accumulation clustering
R Layton, P Watters, R Dazeley
Natural Language Engineering 19 (1), 95-120, 2013
662013
Malicious spam emails developments and authorship attribution
M Alazab, R Layton, R Broadhurst, B Bouhours
2013 fourth cybercrime and trustworthy computing workshop, 58-68, 2013
552013
The Seven Scam Types: Mapping the Terrain of Cybercrime
A Stabek, P Watters, R Layton
Cybercrime and Trustworthy Computing Workshop (CTC), 2010 Second, 41-51, 2010
542010
Characterising and predicting cyber attacks using the Cyber Attacker Model Profile (CAMP)
PA Watters, S McCombie, R Layton, J Pieprzyk
Journal of Money Laundering Control, 2012
492012
Automatically determining phishing campaigns using the USCAP methodology
R Layton, P Watters, R Dazeley
eCrime Researchers Summit (eCrime), 2010, 1-8, 2011
462011
Recentred local profiles for authorship attribution
R Layton, P Watters, R Dazeley
Natural Language Engineering 18 (3), 293-312, 2012
422012
API design for machine learning software: experiences from the scikit-learn project. 2013
L Buitinck, G Louppe, M Blondel, F Pedregosa, A Mueller, O Grisel, ...
arXiv preprint arXiv:1309.0238, 2017
362017
Determining provenance in phishing websites using automated conceptual analysis
R Layton, P Watters
eCrime Researchers Summit, 2009. eCRIME'09., 1-7, 2009
272009
Learning data mining with python
R Layton
Packt Publishing Ltd, 2015
262015
Scikit-learn: machine learning in Python
L Buitinck, G Louppe, M Blondel, F Pedregosa, A Mueller, O Grisel, ...
Journal of Machine Learning Research 12 (85), 2825-2830, 2011
252011
Authorship attribution of irc messages using inverse author frequency
R Layton, S McCombie, P Watters
2012 Third Cybercrime and Trustworthy Computing Workshop, 7-13, 2012
242012
Investigation into the extent of infringing content on BitTorrent networks
R Layton, P Watters
Internet Commerce Security Laboratory, 8-10, 2010
232010
Evaluating authorship distance methods using the positive Silhouette coefficient
R Layton, P Watters, R Dazeley
Natural Language Engineering 19 (4), 517-535, 2013
222013
ECML PKDD Workshop: languages for data mining and machine learning
L Buitinck, G Louppe, M Blondel, F Pedregosa, A Mueller, O Grisel, ...
API Design for Machine Learning Software: Experiences from the Scikit-Learn …, 2013
222013
Unsupervised authorship analysis of phishing webpages
R Layton, P Watters, R Dazeley
2012 International Symposium on Communications and Information Technologies …, 2012
222012
Characterising network traffic for skype forensics
A Azab, P Watters, R Layton
2012 Third cybercrime and trustworthy computing workshop, 19-27, 2012
212012
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