QUT ePrints

Machine learning, neural networks and information security : techniques for extracting rules from trained feedforward Artificial Neural Networks and their application in an information security problem domain

Tickle, Alan Barry (1997) Machine learning, neural networks and information security : techniques for extracting rules from trained feedforward Artificial Neural Networks and their application in an information security problem domain. .

Find a copy in the QUT Library.

Impact and interest:

Citation countsare sourced monthly from Scopus and Web of Science® citation databases.

These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.

Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.

ID Code: 36836
Item Type: QUT Thesis (PhD)
Additional Information: Presented to the School of Computing Science, Queensland University of Technology.
Keywords: Machine learning, Neural networks (Computer science), Computer security, machine learning, artificial neural networks, rule extraction, contribution analysis, coefficient reduction, functional dependencies, object classification, document security, information privacy, thesis, doctoral
Institution: Queensland University of Technology
Copyright Owner: Copyright Alan Barry Tickle
Deposited On: 22 Sep 2010 23:06
Last Modified: 09 Feb 2011 23:56

Export: EndNote | Dublin Core | BibTeX

Repository Staff Only: item control page