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Tytuł pozycji:

Identifying the Effect of Data Breach Publicity on Information Security Awareness Using Hierarchical Regression

Tytuł:
Identifying the Effect of Data Breach Publicity on Information Security Awareness Using Hierarchical Regression
Autorzy:
Hui Na Chua
Jia Sheng Teh
Anthony Herbland
Temat:
Data breach publicity
hierarchical regression
information security awareness
information privacy
Electrical engineering. Electronics. Nuclear engineering
TK1-9971
Źródło:
IEEE Access, Vol 9, Pp 121759-121770 (2021)
Wydawca:
IEEE, 2021.
Rok publikacji:
2021
Kolekcja:
LCC:Electrical engineering. Electronics. Nuclear engineering
Typ dokumentu:
article
Opis pliku:
electronic resource
Język:
English
ISSN:
2169-3536
Relacje:
https://ieeexplore.ieee.org/document/9521493/; https://doaj.org/toc/2169-3536
DOI:
10.1109/ACCESS.2021.3107426
Dostęp URL:
https://doaj.org/article/2f3c795c74c34d33b0c8c36c22e95416  Link otwiera się w nowym oknie
Numer akcesji:
edsdoj.2f3c795c74c34d33b0c8c36c22e95416
Czasopismo naukowe
The technological evolution has formed new challenges for organizations to safeguard their information as digital assets. Information Security Awareness (ISA) is the cognitive state where individuals comprehend information security, threats, and the capability to develop preventive strategies. Prior studies discovered that human mistakes or misbehavior is the most vulnerable link in information security due to insufficient security awareness. There were massive data breaches reported throughout the years globally. Literature shows that individuals will develop their evaluations of risks and sense of security awareness when receiving security risk information such as data breach incidents. These indications motivated us to examine the effect of an unexplored factor, that is, data breach publicity (DBR) on ISA. The purpose of this research is to discover if DBR significantly improves a model’s ability to predict ISA and its magnitude in influencing ISA. A 3-stage hierarchical linear regression approach was used to build up the model with prior known influential factors to predict ISA. To the extent of our knowledge, there is no study reported to date regarding the implication of DBR on ISA. Our main findings reveal that DBR significantly explains 6.7% of ISA and achieves the highest coefficient comparing with prior known factors. Our research contributes to a novel discovery of a new factor that significantly influences ISA and its magnitude in increasing ISA. This discovery implies the need to incorporate the knowledge of data breach incidents into ISA-related educative programs or strategies to increase ISA.

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