dc.contributor.author |
Adeyemi, Ikuesan Richard
|
|
dc.contributor.author |
Abd Razak, Shukor
|
|
dc.contributor.author |
Salleh, Mazleena
|
|
dc.contributor.author |
Venter, H.S. (Hein)
|
|
dc.date.accessioned |
2018-07-20T06:35:36Z |
|
dc.date.available |
2018-07-20T06:35:36Z |
|
dc.date.issued |
2017 |
|
dc.description.abstract |
User attribution, the process of identifying a human in a digital medium, is a research area that has received significant
attention in information security research areas, with a little research focus on digital forensics. This study explored the probability of
the existence of a digital fingerprint based on human thinking style, which can be used to identify an online user. To achieve this, the
study utilized Server-side web data of 43-respondents were collected for 10-months as well as a self-report thinking style
measurement instrument. Cluster dichotomies from five thinking styles were extracted. Supervised machine-learning techniques were
then applied to distinguish individuals on each dichotomy. The result showed that thinking styles of individuals on different
dichotomies could be reliably distinguished on the Internet using a Meta classifier of Logistic model tree with bagging technique. The
study further modelled how the observed signature can be adopted for a digital forensic process, using high-level universal modelling
language modelling process- specifically, the behavioural state-model and use-case modelling process. In addition to the application of
this result in forensics process, this result finds relevance and application in human-centered graphical user interface design for
recommender system as well as in e-commerce services. It also finds application in online profiling processes, especially in e-learning
systems. |
en_ZA |
dc.description.department |
Computer Science |
en_ZA |
dc.description.librarian |
am2018 |
en_ZA |
dc.description.sponsorship |
Universiti Teknologi Malaysia and Ministry of Higher
Education Malaysia under the vote
number: R.J130000.7813.4F804. |
en_ZA |
dc.description.uri |
http://ijaseit.insightsociety.org |
en_ZA |
dc.identifier.citation |
Adeyemi, I.R., Abd Razak, S., Salleh, M. et al. 2017, 'Leveraging human thinking style for user attribution in digital forensic process', International Journal on Advanced Science, Engineering and Information Technology, vol. 7, no. 1, pp. 198-206. |
en_ZA |
dc.identifier.issn |
2088-5334 (print) |
|
dc.identifier.issn |
2460-6952 (online) |
|
dc.identifier.uri |
http://hdl.handle.net/2263/65805 |
|
dc.language.iso |
en |
en_ZA |
dc.publisher |
Indonesian Society for Knowledge and Human Development |
en_ZA |
dc.rights |
Article iis licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. |
en_ZA |
dc.subject |
Sternberg thinking style |
en_ZA |
dc.subject |
Online digital-signature |
en_ZA |
dc.subject |
User attribution |
en_ZA |
dc.subject |
Online user identification |
en_ZA |
dc.subject |
Digital forensic process |
en_ZA |
dc.subject |
Human thinking style |
en_ZA |
dc.title |
Leveraging human thinking style for user attribution in digital forensic process |
en_ZA |
dc.type |
Article |
en_ZA |