Leveraging Human Thinking Style for User Attribution in Digital Forensic Process

Adeyemi Richard Ikuesan, Shukor Abd Razak, Mazleena Salleh, Hein S. Venter


User attribution, the process of identifying a human in a digital medium, is a research area that has receive 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 modeled how the observed signature can be adopted for a digital forensic process, using high-level universal modeling language modeling process- specifically, the behavioral state-model and use-case modeling 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


Sternberg thinking style; online digital-signature; User attribution; online user identification; digital forensic process.

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DOI: http://dx.doi.org/10.18517/ijaseit.7.1.1383


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Published by INSIGHT - Indonesian Society for Knowledge and Human Development