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Expert-interviews led analysis of EEVi - a model for effective visualization in cyber-security

Expert-interviews led analysis of EEVi - a model for effective visualization in cyber-security
Expert-interviews led analysis of EEVi - a model for effective visualization in cyber-security
The area of visualization in cyber-security is advancing at a fast pace. However, there is a lack of standardized guidelines for designing and evaluating the resulting visualizations. Furthermore, limited end-user involvement in the design process leads to visualizations that are generic and often ineffective for cyber-security analysts. Thus, the adoption of the resultant cyber-security visualizations is low and this highlights a major research gap. This paper presents expert-interview based validation of EEVi - a model developed to aid in the design and evaluation process of cyber-security visualizations, with a view to make them more effective for cyber-security analysts. A visualization is considered effective if the characteristics of the visualization are essential for an analyst to competently perform a certain task. Thirteen experts were interviewed (six visualization designers and seven cyber-security analysts) and their feedback guided revisions to the model. The responses were subsequently transposed from qualitative data to quantitive data in order to perform statistical analyses on the overall data. This demonstrated that the perspectives of visualization designers and cyber-security analysts generally agreed in their views of effective characteristics for cyber- security visualization, however there was no statistically significant correlation in their responses.
Cyber-Security, Data Visualization, Qualitative Evaluation, Task and Requirements Analysis, Human Factors
Sethi, Aneesha
d28f4d06-34fe-4b65-b816-d92ccbbff6f3
Wills, Gary
3a594558-6921-4e82-8098-38cd8d4e8aa0
Sethi, Aneesha
d28f4d06-34fe-4b65-b816-d92ccbbff6f3
Wills, Gary
3a594558-6921-4e82-8098-38cd8d4e8aa0

Sethi, Aneesha and Wills, Gary (2017) Expert-interviews led analysis of EEVi - a model for effective visualization in cyber-security. IEEE Symposium on Visualization for Cyber Security, United States. 02 Oct 2017. 8 pp . (doi:10.1109/VIZSEC.2017.8062195).

Record type: Conference or Workshop Item (Paper)

Abstract

The area of visualization in cyber-security is advancing at a fast pace. However, there is a lack of standardized guidelines for designing and evaluating the resulting visualizations. Furthermore, limited end-user involvement in the design process leads to visualizations that are generic and often ineffective for cyber-security analysts. Thus, the adoption of the resultant cyber-security visualizations is low and this highlights a major research gap. This paper presents expert-interview based validation of EEVi - a model developed to aid in the design and evaluation process of cyber-security visualizations, with a view to make them more effective for cyber-security analysts. A visualization is considered effective if the characteristics of the visualization are essential for an analyst to competently perform a certain task. Thirteen experts were interviewed (six visualization designers and seven cyber-security analysts) and their feedback guided revisions to the model. The responses were subsequently transposed from qualitative data to quantitive data in order to perform statistical analyses on the overall data. This demonstrated that the perspectives of visualization designers and cyber-security analysts generally agreed in their views of effective characteristics for cyber- security visualization, however there was no statistically significant correlation in their responses.

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Expert-Interviews Led Analysis of EEVi - A Model for Effective Visualization in Cyber-Security
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Accepted/In Press date: 17 August 2017
Published date: 9 October 2017
Additional Information: © © 2017 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.
Venue - Dates: IEEE Symposium on Visualization for Cyber Security, United States, 2017-10-02 - 2017-10-02
Keywords: Cyber-Security, Data Visualization, Qualitative Evaluation, Task and Requirements Analysis, Human Factors

Identifiers

Local EPrints ID: 413439
URI: http://eprints.soton.ac.uk/id/eprint/413439
PURE UUID: 91f039d3-16a9-4863-a630-e5f7a425dfde
ORCID for Aneesha Sethi: ORCID iD orcid.org/0000-0002-9624-9841
ORCID for Gary Wills: ORCID iD orcid.org/0000-0001-5771-4088

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Date deposited: 24 Aug 2017 16:30
Last modified: 18 Feb 2021 16:46

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Author: Aneesha Sethi ORCID iD
Author: Gary Wills ORCID iD

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