Isaca Updated CDPSE Exam Questions and Answers by taylor

Using hash values with stored personal data best enables an organization to detect changes to the data, because hash values are unique and fixed outputs that are generated from the data using a mathematical algorithm. If the data is altered in any way, even by a single bit, the hash value will change dramatically. Therefore, by comparing the current hash value of the data with the original or expected hash value, the organization can verify the integrity and authenticity of the data. If the hash values match, it means that the data has not been tampered with. If the hash values differ, it means that the data has been corrupted or modified.

The best control to prevent data leakage for a cloud-based HR solution with a mobile application interface is to disable the download of data to the mobile devices. This is because downloading data to the mobile devices increases the risk of data loss, theft, or unauthorized access, especially if the devices are lost, stolen, or compromised. Disabling the download of data to the mobile devices ensures that the data remains in the cloud-based solution, where it can be protected by encryption, access control, and other security measures. The other options are not as effective or sufficient as disabling the download of data to the mobile devices, as they do not address the root cause of the data leakage risk, which is the exposure of data outside the cloud-based solution.

Code review is a primary element of application and software hardening. Code review is a process of examining the source code of an application or software to identify and fix errors, vulnerabilities, or inefficiencies that may compromise its functionality, security, or performance. Code review can help prevent common security risks such as buffer overflows, SQL injections, cross-site scripting, or logic flaws. Code review can also help improve the quality, readability, maintainability, and usability of the code. Code review can be done manually by developers or peers, or automatically by tools such as static code analyzers or code quality checkers.

Vulnerability analysis, database configuration, and software repository are also important for application and software hardening, but they are not primary elements. Vulnerability analysis is a process of identifying and assessing the weaknesses or flaws in an application or software that may expose it to attacks or exploitation. Vulnerability analysis can be done by tools such as vulnerability scanners or penetration testers. Database configuration is a process of setting up and managing the parameters, options, or features of a database system that stores or processes data for an application or software. Database configuration can include aspects such as access control, encryption, backup, recovery, performance tuning, or replication. Software repository is a location where the source code, binaries, or documentation of an application or software are stored and managed. Software repository can facilitate version control, collaboration, distribution, or deployment of the application or software.

The notice provided to customers during data collection is the most important consideration when determining retention periods for personal data, as it reflects the transparency and accountability principles of privacy and the expectations and preferences of the data subjects. The notice should inform the customers about the purposes and legal bases of the data processing, the rights and choices of the customers, and the safeguards and measures to protect the data, including how long the data will be kept and when it will be deleted or disposed of. The notice should also be consistent with the applicable laws and regulations that may prescribe or limit the retention periods for certain types of personal data. The other options are not as important as the notice provided to customers during data collection when determining retention periods for personal data. Sectoral best practices for the industry may provide some guidance or benchmarks for retention periods, but they may not reflect the specific context or needs of the organization or the customers. Data classification standards may help to categorize data according to its sensitivity and value, but they may not indicate how long the data should be retained or deleted. Storage capacity available for retained data may affect the feasibility or cost of retaining data, but it should not determine or override the retention periods based on privacy principles, laws or customer expectations1, p. 99-100 References: 1: CDPSE Review Manual (Digital Version)