To help prevent one job role from having sufficient access to create, modify, and approve payroll data, which of the following practices should be employed?
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A. B. C. D.D.
The practice that should be employed to help prevent one job role from having sufficient access to create, modify, and approve payroll data is called "separation of duties."
Separation of duties is a security principle that involves dividing responsibilities between two or more people to reduce the risk of fraud, errors, or unauthorized actions. In this case, separating the responsibilities of creating, modifying, and approving payroll data between different job roles will prevent a single employee from having enough access to manipulate the data for fraudulent purposes.
For example, one job role might be responsible for entering the payroll data, while another role is responsible for verifying and approving the data before it is processed. By separating these responsibilities, any fraudulent or unauthorized changes to the data would require collusion between the two roles, reducing the likelihood of such an occurrence.
Least privilege is another security principle that involves giving users only the access necessary to perform their job duties, but it may not be sufficient in this case as it does not necessarily prevent a single employee from having access to all aspects of the payroll data.
Job rotation involves rotating employees between different job roles to prevent them from becoming too familiar with a single role and potentially abusing their access, but it may not be practical or effective in preventing the specific risk of payroll data manipulation.
Background checks involve verifying an employee's credentials and history to ensure they are trustworthy and reliable, but they do not directly address the issue of access to payroll data.
In conclusion, the practice of separation of duties should be employed to prevent a single job role from having sufficient access to create, modify, and approve payroll data, thereby reducing the risk of fraud and unauthorized changes to the data.