| 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 | 3877 | 2013 |
| 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 | 212 | 2010 |
| 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 | 106 | 2010 |
| 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 | 105 | 2014 |
| 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 | 75 | 2013 |
| Automated unsupervised authorship analysis using evidence accumulation clustering R Layton, P Watters, R Dazeley Natural Language Engineering 19 (1), 95-120, 2013 | 70 | 2013 |
| 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 15 (4), 430-441, 2012 | 65 | 2012 |
| 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 | 60 | 2010 |
| 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 | 56 | 2011 |
| Recentred local profiles for authorship attribution R Layton, P Watters, R Dazeley Natural Language Engineering 18 (3), 293-312, 2012 | 52 | 2012 |
| Automatically determining phishing campaigns using the USCAP methodology R Layton, P Watters, R Dazeley eCrime Researchers Summit (eCrime), 2010, 1-8, 2011 | 50 | 2011 |
| 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 | 47 | 2013 |
| Learning data mining with python R Layton Packt Publishing Ltd, 2015 | 40 | 2015 |
| Evaluating authorship distance methods using the positive Silhouette coefficient R Layton, P Watters, R Dazeley Natural Language Engineering 19 (4), 517-535, 2013 | 35 | 2013 |
| 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 | 33 | 2012 |
| Characterising network traffic for skype forensics A Azab, P Watters, R Layton 2012 Third cybercrime and trustworthy computing workshop, 19-27, 2012 | 30 | 2012 |
| Identifying cyber predators through forensic authorship analysis of chat logs F Amuchi, A Al-Nemrat, M Alazab, R Layton 2012 Third Cybercrime and Trustworthy Computing Workshop, 28-37, 2012 | 27 | 2012 |
| Determining provenance in phishing websites using automated conceptual analysis R Layton, P Watters eCrime Researchers Summit, 2009. eCRIME'09., 1-7, 2009 | 27 | 2009 |
| Unsupervised authorship analysis of phishing webpages R Layton, P Watters, R Dazeley 2012 International Symposium on Communications and Information Technologies …, 2012 | 26 | 2012 |
| Indirect information linkage for OSINT through authorship analysis of aliases R Layton, C Perez, B Birregah, P Watters, M Lemercier Trends and Applications in Knowledge Discovery and Data Mining: PAKDD 2013 …, 2013 | 25 | 2013 |
Professor Paul WattersCyberstronomy Pty LtdPreverjeni e-poštni naslov na cyberstronomy.com
