Know Your Enemy: User Segmentation Based on Human Aspects of Information Security

Users of information systems are the weakest link in information security. Considering their current information security performance is essential for improving information security training. User segmentation can help to improve information security training by dividing users into smaller groups ba...

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Autores principales:	Damjan Fujs, Simon Vrhovec, Damjan Vavpotic
Formato:	article
Lenguaje:	EN
Publicado:	IEEE 2021
Materias:	Clustering methods computer security data processing data visualization information security information systems Electrical engineering. Electronics. Nuclear engineering TK1-9971
Acceso en línea:	https://doaj.org/article/c86836adbe594e6882787cf71a4372a5
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spelling	oai:doaj.org-article:c86836adbe594e6882787cf71a4372a52021-12-03T00:00:32ZKnow Your Enemy: User Segmentation Based on Human Aspects of Information Security2169-353610.1109/ACCESS.2021.3130013https://doaj.org/article/c86836adbe594e6882787cf71a4372a52021-01-01T00:00:00Zhttps://ieeexplore.ieee.org/document/9623526/https://doaj.org/toc/2169-3536Users of information systems are the weakest link in information security. Considering their current information security performance is essential for improving information security training. User segmentation can help to improve information security training by dividing users into smaller groups based on their information security performance. In this paper, we present a segmented approach for information security training of users. To test the approach, we used data collected from students at a Slovenian university (<inline-formula> <tex-math notation="LaTeX">$\text{N}=165$ </tex-math></inline-formula>) with the Human Aspects of Information Security Questionnaire (HAIS-Q). HAIS-Q data was used to divide users into groups according to their information security performance via clustering. The proposed approach inherently balances adaptation of training to the needs of users and the efforts needed to achieve it which maximizes the key benefits of existing information security training approaches. With improved personalization, it mitigates the challenges related to training boringness and lack of user motivation which are emblematic for traditional information security training approaches. The proposed approach also offers some flexibility regarding the degree of personalization and the efforts related to information security training by fine-tuning the number of user groups. Finally, the proposed approach can help to identify beneficial software security requirements during development of new information systems.Damjan FujsSimon VrhovecDamjan VavpoticIEEEarticleClustering methodscomputer securitydata processingdata visualizationinformation securityinformation systemsElectrical engineering. Electronics. Nuclear engineeringTK1-9971ENIEEE Access, Vol 9, Pp 157306-157315 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Clustering methods computer security data processing data visualization information security information systems Electrical engineering. Electronics. Nuclear engineering TK1-9971
spellingShingle	Clustering methods computer security data processing data visualization information security information systems Electrical engineering. Electronics. Nuclear engineering TK1-9971 Damjan Fujs Simon Vrhovec Damjan Vavpotic Know Your Enemy: User Segmentation Based on Human Aspects of Information Security
description	Users of information systems are the weakest link in information security. Considering their current information security performance is essential for improving information security training. User segmentation can help to improve information security training by dividing users into smaller groups based on their information security performance. In this paper, we present a segmented approach for information security training of users. To test the approach, we used data collected from students at a Slovenian university (<inline-formula> <tex-math notation="LaTeX">$\text{N}=165$ </tex-math></inline-formula>) with the Human Aspects of Information Security Questionnaire (HAIS-Q). HAIS-Q data was used to divide users into groups according to their information security performance via clustering. The proposed approach inherently balances adaptation of training to the needs of users and the efforts needed to achieve it which maximizes the key benefits of existing information security training approaches. With improved personalization, it mitigates the challenges related to training boringness and lack of user motivation which are emblematic for traditional information security training approaches. The proposed approach also offers some flexibility regarding the degree of personalization and the efforts related to information security training by fine-tuning the number of user groups. Finally, the proposed approach can help to identify beneficial software security requirements during development of new information systems.
format	article
author	Damjan Fujs Simon Vrhovec Damjan Vavpotic
author_facet	Damjan Fujs Simon Vrhovec Damjan Vavpotic
author_sort	Damjan Fujs
title	Know Your Enemy: User Segmentation Based on Human Aspects of Information Security
title_short	Know Your Enemy: User Segmentation Based on Human Aspects of Information Security
title_full	Know Your Enemy: User Segmentation Based on Human Aspects of Information Security
title_fullStr	Know Your Enemy: User Segmentation Based on Human Aspects of Information Security
title_full_unstemmed	Know Your Enemy: User Segmentation Based on Human Aspects of Information Security
title_sort	know your enemy: user segmentation based on human aspects of information security
publisher	IEEE
publishDate	2021
url	https://doaj.org/article/c86836adbe594e6882787cf71a4372a5
work_keys_str_mv	AT damjanfujs knowyourenemyusersegmentationbasedonhumanaspectsofinformationsecurity AT simonvrhovec knowyourenemyusersegmentationbasedonhumanaspectsofinformationsecurity AT damjanvavpotic knowyourenemyusersegmentationbasedonhumanaspectsofinformationsecurity
_version_	1718374014670340096

Know Your Enemy: User Segmentation Based on Human Aspects of Information Security

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