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Understanding user behaviour through action sequences : from the usual to the unusual
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Nguyen, Phong H., Turkay, Cagatay, Andrienko, Gennady, Andrienko, Natalia, Thonnard, Olivier and Zouaoui, Jihane (2019) Understanding user behaviour through action sequences : from the usual to the unusual. IEEE Transactions on Visualization and Computer Graphics, 25 (9). doi:10.1109/TVCG.2018.2859969 ISSN 1077-2626.
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WRAP-understanding-user-behaviour-through-action-sequences-Turkay-2020.pdf - Accepted Version - Requires a PDF viewer. Download (2733Kb) | Preview |
Official URL: http://dx.doi.org/10.1109/TVCG.2018.2859969
Abstract
Action sequences, where atomic user actions are represented in a labelled, timestamped form, are becoming a fundamental data asset in the inspection and monitoring of user behaviour in digital systems. Although the analysis of such sequences is highly critical to the investigation of activities in cyber security applications, existing solutions fail to provide a comprehensive understanding due to the complex semantic and temporal characteristics of these data. This paper presents a visual analytics approach that aims to facilitate a user-involved, multi-faceted decision making process during the identification and the investigation of “unusual” action sequences. We first report the results of the task analysis and domain characterisation process. Then we describe the components of our multi-level analysis approach that comprises of constraint-based sequential pattern mining and semantic distance based clustering, and multi-scalar visualisations of users and their sequences. Finally, we demonstrate the applicability of our approach through a case study that involves tasks requiring effective decision-making by a group of domain experts. Although our solution here is tightly informed by a user-centred, domain-focused design process, we present findings and techniques that are transferable to other applications where the analysis of such sequences is of interest.
| Item Type: | Journal Article | ||||||
|---|---|---|---|---|---|---|---|
| Subjects: | Q Science > QA Mathematics > QA75 (Please use QA76 Electronic Computers. Computer Science) | ||||||
| Divisions: | Faculty of Social Sciences > Centre for Interdisciplinary Methodologies | ||||||
| Library of Congress Subject Headings (LCSH): | Sequential pattern mining , Visual analytics, Computer security | ||||||
| Journal or Publication Title: | IEEE Transactions on Visualization and Computer Graphics | ||||||
| Publisher: | Institute of Electrical and Electronics Engineers | ||||||
| ISSN: | 1077-2626 | ||||||
| Official Date: | 25 July 2019 | ||||||
| Dates: |
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| Volume: | 25 | ||||||
| Number: | 9 | ||||||
| DOI: | 10.1109/TVCG.2018.2859969 | ||||||
| Status: | Peer Reviewed | ||||||
| Publication Status: | Published | ||||||
| Reuse Statement (publisher, data, author rights): | © 2019 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. | ||||||
| Access rights to Published version: | Restricted or Subscription Access | ||||||
| Date of first compliant deposit: | 28 May 2020 | ||||||
| Date of first compliant Open Access: | 28 May 2020 | ||||||
| RIOXX Funder/Project Grant: |
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