Software forensics for discriminating between program authors using case-based reasoning, feed-forward neural networks and multiple discriminant analysis

aut.researcherMacDonell, Stephen Gerard
dc.contributor.authorMacDonell, SG
dc.contributor.authorGray, AR
dc.contributor.authorMacLennan, G,
dc.contributor.authorSallis, PJ,
dc.date.accessioned2011-10-04T05:56:32Z
dc.date.available2011-10-04T05:56:32Z
dc.date.copyright1999
dc.date.issued1999
dc.description.abstractSoftware forensics is the field that, by treating pieces of program source code as linguistically and stylistically analyzable entities, attempts to investigate computer program authorship. This can be performed with the goal of identification, discrimination, or characterization of authors. In this paper we extract a set of 26 standard authorship metrics from 351 programs by 7 different authors. The use of feedforward neural networks, multiple discriminant analysis, and case-based reasoning is then investigated in terms of classification accuracy for the authors on both training and testing samples. The first two techniques produce remarkably similar results, with the best results coming from the case-based reasoning models. All techniques have high prediction accuracy rates, supporting the feasibility of the task of discriminating program authors based on source-code measurements
dc.identifier.citationProceedings from the ICONIP '99 6th International Conference on Neural Information Processing (ICONIP'99/ANZIIS'99/ANNES'99/ACNN'99), Perth, Australia, pp.66-71
dc.identifier.doi10.1109/ICONIP.1999.843963
dc.identifier.isbn0-7803-5871-6
dc.identifier.urihttps://hdl.handle.net/10292/2220
dc.publisherIEEE Computer Society Press
dc.relation.urihttp://dx.doi.org/10.1109/ICONIP.1999.843963
dc.rightsCopyright © 1999 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
dc.rights.accessrightsOpenAccess
dc.subjectFeedforward neural networks
dc.subjectFeedforward systems
dc.subjectForensics
dc.subjectInformation analysis
dc.subjectInformation science
dc.subjectNeural networks
dc.subjectPlagiarism
dc.subjectProgramming profession
dc.subjectPsychology
dc.subjectVolume measurement
dc.titleSoftware forensics for discriminating between program authors using case-based reasoning, feed-forward neural networks and multiple discriminant analysis
dc.typeConference Contribution
pubs.organisational-data/AUT
pubs.organisational-data/AUT/Design & Creative Technologies
pubs.organisational-data/AUT/PBRF Researchers
pubs.organisational-data/AUT/PBRF Researchers/Design & Creative Technologies PBRF Researchers
pubs.organisational-data/AUT/PBRF Researchers/Design & Creative Technologies PBRF Researchers/DCT C & M Computing
Files
Original bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
MacDonell, Gray, MacLennan and Sallis (1999) ICONIP.pdf
Size:
196.74 KB
Format:
Adobe Portable Document Format
Description:
License bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
licence.htm
Size:
29.98 KB
Format:
Unknown data format
Description: