The Impact of the Application of IT Governance According to (COBIT 5) Framework in Reduce Cloud Computing Risks
Bibliographic record
Abstract
The study aimed at identifying the impact of the application of IT governance represented by (Planning and Organization, Possessiveness and Implementation, Support and Delivery, Monitoring and Evaluation, and Guidance and Control), using (COBIT 5) framework to reduce the risks associated with cloud computing (Identity and Access Management, Data protection, Virtual operating risk, IT support, and Organization) in the Jordanian industrial companies public shareholding from the perspective of Jordanian Certified Public Accountants. The study follows sequential procedures as a strategy for the mixed methods that have been applied. The researcher collects qualitative data that are quantitatively analyzed. A questionnaire was used to achieve the purpose of the study. The study population included all external accountants practicing auditing in Jordan, who number until the end of 2017 (384), a simple random sample was drawn, the sample included (192) auditors. The study concluded that all the decisions of the (COBIT5) Committee including Planning and Organization, Possessiveness and Implementation, Support and Delivery, Monitoring and Evaluation, and Guidance and Control affect the reduction of the risk of cloud computing in terms of identity and Access Management, Data protection, Virtual operating risk, IT support, and Organization the Jordanian industrial companies public shareholding from the perspective of Jordanian Certified Public Accountants. Based on the findings of the study, the researcher recommends that Jordanian industrial companies need to activate the role of security controls and increase the level of application against the environmental risks surrounding the company likely to occur as a result of the application of cloud computing. It is also necessary to update and develop information technologies, especially those related to technology.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.017 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".