CDPSE Isaca Certified Data Privacy Solutions Engineer Free Practice Exam Questions (2025 Updated)

Sensitive personal data is a subset of personal data that reveals or relates to more intimate or confidential aspects of a person’s identity, such as their racial or ethnic origin, religious or philosophical beliefs, health status, sexual orientation, political opinions, trade union membership, biometric or genetic data, or criminal record. Sensitive personal data is subject to more stringent legal and regulatory protections and requires a higher level of consent from the data subject to be processed. Mailing address, bank account login ID, and contact phone number are examples of personal data, but not sensitive personal data, as they do not reveal or relate to such intimate or confidential aspects of a person’s identity.

References: CDPSE Review Manual, 2021, p. 29

A privacy impact assessment (PIA) is a systematic process of identifying and evaluating the potential privacy risks and impacts of a data processing activity or system. A PIA helps to ensure that privacy is considered and integrated into the design and development of data processing activities or systems, and that privacy risks are mitigated or eliminated. A PIA also helps to determine the appropriate retention periods for personal data based on the purpose and necessity of the data processing, as well as the legal and regulatory obligations that apply to the data. Therefore, a PIA helps to define data retention time in a stream-fed data lake that includes personal data. References: : CDPSE Review Manual (Digital Version), page 99

An analysis of known threats is the best way for an organization to gain visibility into its exposure to privacy-related vulnerabilities because it helps identify the sources, methods and impacts of potential privacy breaches and assess the effectiveness of existing controls. A data loss prevention (DLP) solution, a review of historical privacy incidents and a monitoring of inbound and outbound communications are useful tools for detecting and preventing privacy violations, but they do not provide a comprehensive view of the organization’s privacy risk posture.

References:

CDPSE Review Manual (Digital Version), Domain 1: Privacy Governance, Task 1.4: Coordinate and/or perform privacy impact assessments (PIA) and other privacy-focused assessments1

CDPSE Certified Data Privacy Solutions Engineer All-in-One Exam Guide, Chapter 2: Privacy Governance, Section: Privacy Risk Assessment2

The role primarily assigned to an internal data owner is authorizing access rights. A data owner is a person or a role within the organization who has the authority and responsibility for the data assets under their control. A data owner is responsible for defining the data classification, data quality, data retention, and data security requirements for their data assets. A data owner is also responsible for granting, revoking, and reviewing the access rights to their data assets based on the principle of least privilege and the business needs. A data owner is accountable for ensuring that the data assets are used in compliance with the organizational policies and the applicable laws and regulations. References:

[ISACA Glossary of Terms]

[ISACA CDPSE Review Manual, Chapter 3, Section 3.2.1]

[ISACA CDPSE Review Manual, Chapter 3, Section 3.2.2]

[ISACA CDPSE Review Manual, Chapter 3, Section 3.2.3]

The primary consideration of a multinational organization deploying a user and entity behavior analytics (UEBA) tool to centralize the monitoring of anomalous employee behavior is cross-border data transfer, because it may involve the transfer of personal data across different jurisdictions with different privacy laws and regulations. The organization needs to ensure that it complies with the applicable legal requirements and safeguards the privacy rights of its employees when transferring their data to a central location for analysis. The other options are secondary or operational considerations that may not have a significant impact on the privacy of the employees.

References:

CDPSE Exam Content Outline, Domain 2 – Privacy Architecture (Privacy Architecture Implementation), Task 3: Implement privacy solutions1.

CDPSE Review Manual, Chapter 2 – Privacy Architecture, Section 2.4 – Cross-Border Data Transfer2.

CDPSE Certified Data Privacy Solutions Engineer All-in-One Exam Guide, Chapter 2 – Privacy Architecture, Section 2.5 – Cross-Border Data Transfer3.

From a privacy perspective, it is most important to ensure data backups are encrypted. Encryption is a process of transforming data into an unreadable form using a secret key or algorithm. Encryption can help protect the confidentiality, integrity, and availability of data backups by preventing unauthorized access, disclosure, or modification. Encryption can also help comply with legal and regulatory requirements for data protection, such as the General Data Protection Regulation (GDPR) or the Health Insurance Portability and Accountability Act (HIPAA). Encryption can be applied to data backups at different levels, such as file-level, disk-level, or network-level encryption.

Incremental backups, differential backups, or pseudonymization are also useful for data backup management, but they are not the most important from a privacy perspective. Incremental backups are backups that only copy the data that has changed since the last backup, whether it was a full, differential, or incremental backup. Incremental backups can help save storage space and time, but they do not directly protect the data from unauthorized access or disclosure. Differential backups are backups that only copy the data that has changed since the last full backup. Differential backups can also help save storage space and time, but they also do not directly protect the data from unauthorized access or disclosure. Pseudonymization is a process of replacing identifying information in data with artificial identifiers or pseudonyms. Pseudonymization can help enhance the privacy of data by reducing the linkability between data and data subjects, but it does not prevent re-identification or inference attacks.

References: Data backups 101: A complete guide for 2023 - Norton, Backup & Secure | U.S. Geological Survey - USGS.gov, The GDPR: How the right to be forgotten affects backups

Encryption of network traffic is the most important control to mitigate the risk of potential personal data compromise when employees access corporate IT assets remotely. Encryption is a process that transforms data into an unreadable form, making it difficult for unauthorized parties to intercept, modify, or steal it. Encryption of network traffic ensures that the data transmitted between the remote employees and the corporate network is protected from eavesdropping, tampering, or leakage.

Intrusion prevention system (IPS), firewall rules review, and intrusion detection system (IDS) are also useful controls for network security, but they are not as effective as encryption for protecting personal data in transit. IPS and IDS can monitor and block malicious or suspicious network traffic, but they cannot prevent data exposure if the traffic is intercepted by a third party. Firewall rules review can help optimize and secure the firewall configuration, but it cannot guarantee that the firewall will not be bypassed or compromised by an attacker. Therefore, encryption of network traffic is the best option among the choices given.

Conducting a privacy impact assessment (PIA) should be done first to establish privacy by design when developing a contact-tracing application. A PIA is a systematic process that identifies and evaluates the potential effects of personal data processing operations on the privacy of individuals and the organization. A PIA helps to identify privacy risks and mitigation strategies at an early stage of development and ensures compliance with legal and regulatory requirements. Conducting a development environment review, identifying privacy controls, or identifying differential privacy techniques are important steps in privacy by design, but they should be done after conducting a PIA. References: CDPSE Exam Content Outline, Domain 2, Task 2.1

Privacy threat modeling is a methodology for identifying and mitigating privacy threats in a software architecture. It helps to ensure that privacy is considered in the design and development of software systems, and that privacy risks are minimized or eliminated. Privacy threat modeling typically involves the following steps: defining the scope and context of the system, identifying the data flows and data elements, identifying the privacy threats and their sources, assessing the impact and likelihood of the threats, and applying appropriate countermeasures to mitigate the threats. References: : CDPSE Review Manual (Digital Version), page 97

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

The principle of least privilege is the most important principle to apply when granting access to an ERP system that contains a significant amount of personal data. The principle of least privilege states that users should only have the minimum level of access and permissions necessary to perform their legitimate tasks and functions, and no more. Applying the principle of least privilege helps to protect the privacy and security of the personal data in the ERP system, as it reduces the risk of unauthorized or inappropriate access, disclosure, modification, or deletion of the data. It also helps to comply with the privacy laws and regulations, such as the GDPR, that require data controllers and processors to implement appropriate technical and organizational measures to ensure a level of security appropriate to the risk.

References: CDPSE Review Manual, 2021, p. 132

A data processor that handles personal data for multiple customers has decided to migrate its data warehouse to a third-party provider. The processor is obligated to seek approval from all in-scope data controllers prior to implementation. A data controller is an entity that determines the purposes and means of processing personal data. A data processor is an entity that processes personal data on behalf of a data controller. A third-party provider is an entity that provides services or resources to another entity, such as a cloud service provider or a hosting provider.

According to various privacy laws and regulations, such as the GDPR or the CCPA, a data processor must obtain explicit consent from the data controller before engaging another processor or transferring personal data to a third country or an international organization. The consent must specify the identity of the other processor or the third country or international organization, as well as the safeguards and guarantees for the protection of personal data. The consent must also be documented in a written contract or other legal act that binds the processor to respect the same obligations as the controller.

Seeking approval from all in-scope data controllers can help ensure that the processor complies with its contractual and legal obligations, respects the rights and preferences of the data subjects, and maintains transparency and accountability for its processing activities.

Obtaining assurance that data subject requests will continue to be handled appropriately, implementing comparable industry-standard data encryption in the new data warehouse, or ensuring data retention periods are documented are also good practices for a data processor that migrates its data warehouse to a third-party provider, but they are not obligations prior to implementation. Rather, they are requirements or recommendations during or after implementation.

Obtaining assurance that data subject requests will continue to be handled appropriately is a requirement for a data processor that processes personal data on behalf of a data controller. Data subject requests are requests made by individuals to exercise their rights regarding their personal data, such as access, rectification, erasure, restriction, portability, or objection. A data processor must assist the data controller in fulfilling these requests within a reasonable time frame and without undue delay.

Implementing comparable industry-standard data encryption in the new data warehouse is a recommendation for a data processor that transfers personal data to another system or location. Data encryption is a process of transforming data into an unreadable form using a secret key or algorithm. Data encryption can help protect the confidentiality, integrity, and availability of personal data by preventing unauthorized access, disclosure, or modification.

Ensuring data retention periods are documented is a requirement for a data processor that stores personal data on behalf of a data controller. Data retention periods are the durations for which personal data are kept before they are deleted or anonymized. Data retention periods must be determined by the purpose and necessity of processing personal data and must comply with legal and regulatory obligations.

References: Data warehouse migration tips: preparation and discovery - Google Cloud, Plan a data warehouse migration - Cloud Adoption Framework, Migrating your traditional data warehouse platform to BigQuery …

Implementing multi-factor authentication is the best way to reduce the risk of compromised credentials when an organization allows employees to have remote access, as it adds an extra layer of security and verification to the authentication process. Multi-factor authentication requires the user to provide two or more pieces of evidence to prove their identity, such as something they know (e.g., password, PIN), something they have (e.g., token, smart card), or something they are (e.g., fingerprint, face scan)135. References: 1 Domain 2, Task 8;

The practice that best indicates an organization follows the data minimization principle is that data is regularly reviewed for its relevance. The data minimization principle is one of the core principles of data protection under various laws and regulations, such as the GDPR or the CCPA. It states that personal data should be adequate, relevant, and limited to what is necessary in relation to the purposes for which they are processed. By regularly reviewing the data they hold, organizations can ensure that they do not collect or retain excessive or unnecessary data that may pose privacy risks or violate data subject rights.

Data is pseudonymized when being backed up, data is encrypted before storage, or data is only accessible on a need-to-know basis are also good practices for data protection, but they do not directly indicate that the organization follows the data minimization principle. Pseudonymization is a process of replacing identifying information in data with artificial identifiers or pseudonyms. Pseudonymization can help enhance the privacy of data by reducing the linkability between data and data subjects, but it does not prevent re-identification or inference attacks. Encryption is a process of transforming data into an unreadable form using a secret key or algorithm. Encryption can help protect the confidentiality, integrity, and availability of data by preventing unauthorized access, disclosure, or modification. Access control is a process of restricting who can access, modify, or delete data based on their roles, permissions, or credentials. Access control can help prevent unauthorized or inappropriate use of data by limiting the scope of access.

References: Data Minimization | Washington Technology Solutions, What Is Data Minimization? The Principles According to GDPR | 2BAdvice, Data Protection Principles: Core Principles of the GDPR - Cloudian

According to the General Data Protection Regulation (GDPR), data subjects have the right to withdraw their consent for processing their personal data at any time. However, this right does not apply when the processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes, in accordance with Article 89(1) of the GDPR1.

References: 1: Article 7(3) and Article 89(1) of the GDPR

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.

References: CDPSE Review Manual, 2021, p. 128

A privacy impact assessment (PIA) is a process of analyzing the potential privacy risks and impacts of collecting, using, and disclosing personal data. A PIA should be conducted when there is a change in the data processing activities that may affect the privacy of individuals or the compliance with data protection laws and regulations. One of the scenarios that should trigger the completion of a PIA is when there are new inter-organizational data flows, which means that personal data is shared or transferred between different entities or jurisdictions. This may introduce new privacy risks, such as unauthorized access, misuse, or breach of data, as well as new legal obligations, such as obtaining consent, ensuring adequate safeguards, or notifying authorities.

References:

PIA Triggers - International Association of Privacy Professionals

Privacy Impact Assessment - International Association of Privacy Professionals

GDPR Privacy Impact Assessment

Data Protection Impact Assessment triggers: Clarity or confusion?