A validation of security determinants model for cloud adoption in Saudi organisations’ context

Journal article


Alassafi, Madini O., Atlam, Hany F., Alshdadi, Abdulrahman A., Alzahrani, Abdullah I., AlGhamdi, Rayed A. and Buhari, Seyed M. 2019. A validation of security determinants model for cloud adoption in Saudi organisations’ context. International Journal of Information Technology. https://doi.org/10.1007/s41870-019-00360-4
AuthorsAlassafi, Madini O., Atlam, Hany F., Alshdadi, Abdulrahman A., Alzahrani, Abdullah I., AlGhamdi, Rayed A. and Buhari, Seyed M.
Abstract

Governments across the world are starting to make a dynamic shift to cloud computing so as to increase efficiency. Although, the cloud technology brings various benefits for government organisations, including flexibility and low cost, adopting it with the existing system is not an easy task. In this regard, the most significant challenge to any government agency is security concern. Our previous study focused to identify security factors that influence decision of government organisations to adopt cloud. This research enhances the previous work by investigating on the impact of various independent security related factors on the adopted security taxonomy based on critical ratio, standard error and significance levels. Data was collected from IT and security experts in the government organisations of Saudi Arabia. The Analysis of Moment Structures (AMOS) tool was used in this research for data analysis. Critical ratio reveals the importance of Security Benefits, Risks and Awareness Taxonomies on cloud adoption. Also, most of the exogenous variables had strong and positive relationships with their fellow exogenous variables. In future, this taxonomy model can also be applied for studying the adoption of new IT innovations whose IT architecture is similar to that of the cloud.

KeywordsCloud security factors; Cloud adoption; Structure equation modelling; Saudi government organisations
Year2019
JournalInternational Journal of Information Technology
PublisherSpringer
ISSN25112104
Digital Object Identifier (DOI)https://doi.org/10.1007/s41870-019-00360-4
Web address (URL)http://hdl.handle.net/10545/624239
http://creativecommons.org/licenses/by-nd/4.0/
hdl:10545/624239
Publication dates30 Aug 2019
Publication process dates
Deposited24 Oct 2019, 13:34
Accepted23 Aug 2019
Rights

Attribution-NoDerivatives 4.0 International

ContributorsUniversity of Southampton
File
File Access Level
Open
File
File Access Level
Open
Permalink -

https://repository.derby.ac.uk/item/940v6/a-validation-of-security-determinants-model-for-cloud-adoption-in-saudi-organisations-context

Download files

  • 41
    total views
  • 0
    total downloads
  • 1
    views this month
  • 0
    downloads this month

Export as

Related outputs

Deep labeller: automatic bounding box generation for synthetic violence detection datasets
Nadeem, M., Kurugollu, F., Saravi, S., Atlam, H. and Franqueira, V. 2023. Deep labeller: automatic bounding box generation for synthetic violence detection datasets. Multimedia Tools and Applications. pp. 1-18. https://doi.org/10.1007/s11042-023-15621-5
Business Email Compromise Phishing Detection Based on Machine Learning: A Systematic Literature Review
Atlam, H. and Olayonu Oluwatimilehin 2022. Business Email Compromise Phishing Detection Based on Machine Learning: A Systematic Literature Review. Electronics. 12 (1), pp. 1-28. https://doi.org/10.3390/electronics12010042
ANFIS for risk estimation in risk-based access control model for smart homes
Atlam, H. and Gary B. Wills 2022. ANFIS for risk estimation in risk-based access control model for smart homes. Multimedia Tools and Applications. pp. 1-30. https://doi.org/10.1007/s11042-022-14010-8
DEEPSEL: A novel feature selection for early identification of malware in mobile applications
Muhammad Ajmal Azad, Farhan Riaz, Anum Aftab, Syed Khurram Jah Rizvi, Junaid Arshad, Hany F. Atlam and Atlam, H. 2021. DEEPSEL: A novel feature selection for early identification of malware in mobile applications. Future Generation Computer Systems. 129, pp. 54-63. https://doi.org/10.1016/j.future.2021.10.029
IoT forensics: A state-of-the-art review, callenges and future directions
Alenezi, Ahmed, Atlam, Hany, Alsagri, Reem, Alassafi, Madini and Wills, Gary 2019. IoT forensics: A state-of-the-art review, callenges and future directions. SCITEPRESS - Science and Technology Publications. https://doi.org/10.5220/0007905401060115
Experts reviews of a cloud forensic readiness framework for organizations
Alenezi, Ahmed, Atlam, Hany F. and Wills, Gary B. 2019. Experts reviews of a cloud forensic readiness framework for organizations. Journal of Cloud Computing. 8 (1). https://doi.org/10.1186/s13677-019-0133-z
Security, cybercrime and digital forensics for IoT
Atlam, Hany F., Alenezi, Ahmed, Alassafi, Madini O., Alshdadi, Abdulrahman A. and Wills, Gary B. 2019. Security, cybercrime and digital forensics for IoT. in: Intelligent Systems Reference Library Springer International Publishing.
A famework for data sharing between healthcare providers using blockchain
Alzahrani, Ahmed G., Alenezi, Ahmed, Atlam, Hany F. and Wills, Gary 2020. A famework for data sharing between healthcare providers using blockchain. Proceedings of the 5th International Conference on Internet of Things, Big Data and Security. https://doi.org/10.5220/0009413403490358
Intersections between IoT and distributed ledger
Atlam, Hany F. and Wills, Gary B. 2019. Intersections between IoT and distributed ledger. in: Advances in Computers Elsevier.
IoT security, privacy, safety and ethics
Atlam, Hany F. and Wills, Gary B. 2019. IoT security, privacy, safety and ethics. in: Internet of Things Springer International Publishing.
Fuzzy logic with expert judgment to implement an adaptive risk-based access control model for IoT
Atlam, Hany F., Walters, Robert J., Wills, Gary B. and Daniel, Joshua 2019. Fuzzy logic with expert judgment to implement an adaptive risk-based access control model for IoT. Mobile Networks and Applications. https://doi.org/10.1007/s11036-019-01214-w
An efficient security risk estimation technique for Risk-based access control model for IoT
Atlam, Hany F. and Wills, Gary 2019. An efficient security risk estimation technique for Risk-based access control model for IoT. Internet of Things. https://doi.org/10.1016/j.iot.2019.100052