CDPSE Exam Dumps - Certified Data Privacy Solutions Engineer

However, the risks associated with long-term retention have compelled organizations to consider alternatives; one is data archival, the process of preparing data for long-term storage. When organizations are bound by specific laws to retain data for many years, archival provides a viable opportunity to remove data from online transaction systems to other systems or media.

Data archiving is the process of moving data that is no longer actively used to a separate storage device for long-term retention. Data archiving helps to reduce the cost and complexity of data storage, improve the performance and availability of data systems, and comply with data retention policies and regulations. Data archiving should document controls relating to periods of retention for personal data, such as the criteria for determining the retention period, the procedures for deleting or anonymizing data after the retention period expires, and the mechanisms for ensuring the integrity and security of archived data. References: : CDPSE Review Manual (Digital Version), page 123

A data dictionary is a document that defines and describes the data elements, attributes, formats, sources, destinations, purposes and relationships of a data set or system. A data dictionary would be the best way to ensure personal data usage is standardized across the entire organization, as it would provide a common and consistent understanding and reference for how personal data is collected, used, disclosed and transferred within and outside the organization. A data dictionary would also help to ensure compliance with privacy principles, such as accuracy, transparency and accountability. The other options are not as effective as developing a data dictionary in ensuring personal data usage is standardized across the entire organization. De-identify all data is a technique that removes or modifies direct and indirect identifiers in a data set to prevent or limit the identification of the data subjects, but it does not ensure standardization or consistency of personal data usage across the organization. Encrypt all sensitive data is a technique that transforms plain text data into cipher text using an algorithm and a key, making it unreadable by unauthorized parties, but it does not ensure standardization or consistency of personal data usage across the organization. Perform data discovery is a process of identifying and locating personal data within an organization’s systems, databases, applications or files, but it does not ensure standardization or consistency of personal data usage across the organization1, p. 69-70 References: 1: CDPSE Review Manual (Digital Version)

Classifying sensitive unstructured data should be done first to address the situation of the proliferation of personal data held as unstructured data, as it helps to identify the types, locations, and owners of the data, and to apply the appropriate privacy controls and measures based on the data classification level. Classifying sensitive unstructured data also facilitates the data discovery, data minimization, data retention, and data disposal processes. References: 2 Domain 3, Task 2; 5 Page 9

Before using data from the organization’s customer database for a new marketing application, the first step should be to determine what data is required by the application and for what purpose. This will help to ensure that the data collection and processing are relevant, necessary, and proportionate to the intended use, and that the data minimization principle is followed. Data minimization means that only the minimum amount of personal data needed to achieve a specific purpose should be collected and processed, and that any excess or irrelevant data should be deleted or anonymized1. This will also help to comply with the data privacy laws and regulations that apply to the organization, such as the General Data Protection Regulation (GDPR) or the California Consumer Privacy Act (CCPA), which require organizations to inform data subjects about the types and purposes of data processing, and to obtain their consent if needed23.

References:

• ISACA, Data Privacy Audit/Assurance Program, Control Objective 2: Data Minimization, p. 61
• ISACA, GDPR Data Protection Impact Assessments, p. 4-52
• ISACA, CCPA vs. GDPR: Similarities and Differences, p. 1-23

The first consideration for ensuring that endpoints are protected in line with the privacy policy is hardening the operating systems of endpoint devices. Hardening is a process of applying security configurations and controls to reduce the attack surface and vulnerabilities of an operating system. Hardening can include disabling unnecessary services and features, applying security patches and updates, enforcing strong passwords and encryption, configuring firewall and antivirus settings, and implementing least privilege principles. Hardening the operating systems of endpoint devices can help prevent unauthorized access, data leakage, malware infection, or other threats that may compromise the privacy of personal data stored or processed on those devices.

Detecting malicious access through endpoints, implementing network traffic filtering on endpoint devices, and managing remote access and control are also important aspects of endpoint security, but they are not the first consideration. Rather, they are dependent on or complementary to hardening the operating systems of endpoint devices. For example, detecting malicious access requires having a baseline of normal activity and behavior on the endpoint device, which can be established by hardening. Implementing network traffic filtering requires having a firewall or other network security tool installed and configured on the endpoint device, which is part of hardening. Managing remote access and control requires having authentication and authorization mechanisms in place on the endpoint device, which is also part of hardening.

References: Manage endpoint security policies in Microsoft Intune, ENDPOINT SECURITY POLICY, How To Build An Effective Endpoint Security Policy And Prevent Cyberattacks

Restricting access to authorized users is the best control to secure application programming interfaces (APIs) that may contain personal information, as it would prevent unauthorized access, modification or disclosure of the personal information by third parties or intermediaries. Restricting access to authorized users can be achieved by using various methods, such as authentication, authorization, encryption, tokens or certificates. The other options are not effective controls to secure APIs that may contain personal information. Encrypting APIs with the organization’s private key is not a feasible or desirable method, as it would make the APIs unreadable by anyone who does not have the corresponding public key, which would defeat the purpose of using APIs for interoperability and integration. Requiring nondisclosure agreements (NDAs) when sharing APIs is not a reliable or enforceable method, as it would depend on the compliance and cooperation of the parties who receive the APIs, and it would not prevent unauthorized access, modification or disclosure of the personal information by third parties or intermediaries who are not bound by the NDAs. Sharing only digitally signed APIs is not a sufficient method, as it would only ensure the authenticity and integrity of the APIs, but it would not prevent unauthorized access, modification or disclosure of the personal information by third parties or intermediaries who can read or intercept the APIs1, p. 90-91 References: 1: CDPSE Review Manual (Digital Version)

Validating the privacy framework is a responsibility of the audit function in helping an organization address privacy compliance requirements, as it would help to verify and validate the effectiveness and adequacy of the privacy framework implemented by the organization to comply with privacy principles, laws and regulations. Validating the privacy framework would also help to identify and report any gaps, weaknesses or issues in the privacy framework, and to provide recommendations for improvement or remediation. The other options are not responsibilities of the audit function in helping an organization address privacy compliance requirements. Approving privacy impact assessments (PIAs) is a responsibility of management or governance function in helping an organization address privacy compliance requirements, as they would have authority and accountability for approving PIAs conducted by project teams or business units before implementing any system, project, program or initiative that involves personal data processing activities. Managing privacy notices provided to customers is a responsibility of operational function in helping an organization address privacy compliance requirements, as they would have direct contact and interaction with customers and would be responsible for providing clear and accurate information about how their personal data is collected, used, disclosed and transferred by the organization. 

De-identification is a technique that removes or modifies direct and indirect identifiers in a data set to prevent or limit the identification of the data subjects. De-identification reduces the risk of re-identification and thus limits the organization’s potential exposure in the event of consumer data loss. De-identification also maintains the traceability of the data by preserving some characteristics or patterns of the original data that can be used for analysis or research purposes. The other options are not effective ways to limit exposure and maintain traceability1, p. 75-76 References: 1: CDPSE Review Manual (Digital Version)