Survey and critique of techniques for extracting rules from trained artificial neural networks R Andrews, J Diederich, AB Tickle Knowledge-based systems 8 (6), 373-389, 1995 | 1648 | 1995 |
The truth will come to light: Directions and challenges in extracting the knowledge embedded within trained artificial neural networks AB Tickle, R Andrews, M Golea, J Diederich IEEE Transactions on Neural Networks 9 (6), 1057-1068, 1998 | 580 | 1998 |
Using a Network Simulation Tool to engage students in Active Learning enhances their understanding of complex data communications concepts. C Goldstein, S Leisten, K Stark, A Tickle ACE 5, 223-228, 2005 | 74 | 2005 |
DEDEC: decision detection by rule extraction from neural networks AB Tickle, M Orlowski, J Diederich QUT NRC, 1994 | 57 | 1994 |
A framework for generating realistic traffic for Distributed Denial-of-Service attacks and Flash Events S Bhatia, D Schmidt, G Mohay, A Tickle computers & security 40, 95-107, 2014 | 56 | 2014 |
Parametric differences between a real-world distributed denial-of-service attack and a flash event S Bhatia, G Mohay, A Tickle, E Ahmed 2011 sixth international conference on availability, reliability and …, 2011 | 54 | 2011 |
DEDEC: A methodology for extracting rules from trained artificial neural networks AB Tickle, M Orlowski, J Diederich Neurocomputing Research Centre, Queensland University of Technology, 1996 | 49 | 1996 |
Lessons from past, current issues, and future research directions in extracting the knowledge embedded in artificial neural networks AB Tickle, F Maire, G Bologna, R Andrews, J Diederich Hybrid neural systems, 226-239, 2000 | 35 | 2000 |
Use of ip addresses for high rate flooding attack detection E Ahmed, G Mohay, A Tickle, S Bhatia Security and Privacy–Silver Linings in the Cloud: 25th IFIP TC-11 …, 2010 | 31 | 2010 |
Rule extraction from trained artificial neural networks R Andrews Neural network analysis, architectures and algorithms, 61-99, 1997 | 29 | 1997 |
Modelling web-server flash events S Bhatia, G Mohay, D Schmidt, A Tickle 2012 IEEE 11th International Symposium on Network Computing and Applications …, 2012 | 26 | 2012 |
An evaluation and comparison of techniques for extracting and refining rules from artificial neural networks R Andrews, R Cable, J Diederich, S Geva, M Golea, R Hayward, ... QUT NRC (February 1996), 1996 | 26 | 1996 |
A distributed denial of service testbed D Schmidt, S Suriadi, A Tickle, A Clark, G Mohay, E Ahmed, J Mackie What Kind of Information Society? Governance, Virtuality, Surveillance …, 2010 | 24 | 2010 |
The risk data repository: a novel approach to security risk modelling A Anderson, D Longley, AB Tickle Proceedings of the IFIP TC11, Ninth International Conference on Information …, 1993 | 18 | 1993 |
The truth is in there: current issues in extracting rules from trained feedforward artificial neural networks AB Tickle, M Golea, R Hayward, J Diederich Proceedings of International Conference on Neural Networks (ICNN'97) 4, 2530 …, 1997 | 15 | 1997 |
A methodology for describing information and physical security architectures WJ Caelli, D Longley, AB Tickle Proceedings of the IFIP TC11, Eigth International Conference on Information …, 1992 | 15 | 1992 |
Animation of complex data communications concepts may not always yield improved learning outcomes G Dowling, A Tickle, K Stark, J Rowe, M Godat Proceedings of the 7th Australasian Conference on Computing Education, 151-154, 2005 | 14 | 2005 |
Quo vadis? Reliable and practical rule extraction from neural networks J Diederich, AB Tickle, S Geva Advances in Machine Learning I: Dedicated to the Memory of Professor Ryszard …, 2010 | 11 | 2010 |
Rule-Extraction from trained neural networks: Different techniques for the determination of herbicides for the plant protection advisory system PRO_PLANT U Visser, A Tickle, R Hayward, R Andrews Proc. of the rule extraction from trained ANN workshop, Brighton, UK, 133-139, 1996 | 10 | 1996 |
Extracting rules for grammar recognition from cascade-2 networks R Hayward, A Tickle, J Diederich Connectionist, Statistical and Symbolic Approaches to Learning for Natural …, 1996 | 10 | 1996 |