Free CDPSE Practice Test Questions and Answers (2026) | Cert Empire Practice Questions

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.

Reference:

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.

User consent to share personal data is the most important factor when designing APIs that enable

mobile device applications to access personal data, as it ensures that the user is informed and agrees

to the purpose, scope, and duration of the data sharing. User consent also helps to comply with the

data protection principles and regulations, such as the General Data Protection Regulation (GDPR)

and the California Consumer Privacy Act (CCPA), that require user consent for certain types of data

processing and sharing134. Reference: 1 Domain 2, Task 7

Public key infrastructure (PKI) is a system that enables the use of public key cryptography, which is a

method of encrypting and authenticating data using a pair of keys: a public key and a private key.

Public key cryptography can protect against man-in-the-middle (MITM) attacks, which are attacks

where an attacker intercepts and modifies the communication between two parties. PKI makes

public key cryptography feasible by providing a way to generate, distribute, verify, and revoke public

keys. PKI also uses digital certificates, which are documents that bind a public key to an identity, and

certificate authorities, which are trusted entities that issue and validate certificates. By using PKI, the

parties can ensure that they are communicating with the intended recipient and that the data has

not been tampered with by an attacker.

Reference:

What is Public Key Infrastructure (PKI)? - Fortinet

How is man-in-the-middle attack prevented in TLS? [duplicate]

A brief look at Man-in-the-Middle Attacks and the Role of Public Key Infrastructure (PKI)

D. Requiring employees to review the organization’s privacy policy on an annual basis

Short Requiring employees to review the organization’s privacy policy on an annual basis is the best

activity to enable an organization to identify gaps in its privacy posture because it can help to ensure

that the employees are aware of the current privacy requirements, expectations, and practices of the

organization. It can also help to identify any discrepancies, inconsistencies, or conflicts between the

policy and the actual implementation of privacy controls and processes. By reviewing the policy

regularly, the organization can also update and improve it as needed to reflect any changes in the

privacy landscape, such as new laws, regulations, standards, or threats.

Reference:

Privacy Policy Review Checklist, PrivacySense

How to Write a Privacy Policy for Your Website, TermsFeed

The best way to ensure an effective data privacy policy is implemented is to align regulatory

requirements with business needs, because this will help achieve compliance while also supporting

the organization’s objectives, values, and strategies. A data privacy policy should reflect the legal

obligations and expectations of the organization, as well as the needs and p

of its

stakeholders, such as customers, employees, partners, and regulators. A data privacy policy should

also be flexible and adaptable to changing circumstances and environments12.

Reference:

CDPSE Exam Content Outline, Domain 1 – Privacy Governance (Governance, Management & Risk

Management), Task 3: Participate in the evaluation of privacy policies, programs and policies for their

alignment with legal requirements, regulatory requirements and/or industry best practices3.

CDPSE Review Manual, Chapter 1 – Privacy Governance, Section 1.2 – Privacy Policy4.

An audit log is a record of the activities and events that occur in an information system, such as an

application hosting personal dat

a. An audit log can help to monitor, detect, investigate and prevent unauthorized or malicious access,

use, modification or deletion of personal data. An audit log can also help to demonstrate compliance

with data protection laws and regulations, such as the General Data Protection Regulation (GDPR) or

the California Consumer Privacy Act (CCPA). An audit log should capture the following information

for each event: 9

The date and time of the event

The identity of the user or system that performed the event

The type and description of the event

The outcome or result of the event

The personal data that were accessed, used, modified or deleted

The last user who accessed personal data is the most important information to capture in the audit

log, as it can help to identify who is responsible for any data breach or misuse of personal data. It can

also help to verify that only authorized and legitimate users have access to personal data, and that

they follow the data use policy and the principle of least privilege. The last user who accessed

personal data can also help to support data subjects’ rights, such as the right to access, rectify, erase

or restrict their personal data.

The other options are less important or irrelevant to capture in the audit log of an application hosting

personal data. Server details of the hosting environment are not related to personal data, and they

can be obtained from other sources, such as network logs or configuration files. Last logins of

privileged users are important to capture in a separate audit log for user account management, but

they do not indicate what personal data were accessed or used by those users. Application error

events are important to capture in a separate audit log for system performance and reliability, but

they do not indicate what personal data were affected by those errors.

Reference:

IS Audit Basics: Auditing Data Privacy, section 4: “Audit logs should be maintained for all systems that

process PII.”

Data Protection Audit Manual, section 3.2: “Audit trails should be kept for all processing operations

involving personal data.”

Audit Logging Best Practices, section 2: “An audit log entry should contain enough information to

answer who did what and when.”

Data loss prevention (DLP) tools are technologies that help to prevent unauthorized access, use, or

transfer of personal dat

a. DLP tools can monitor, detect, and block data leakage or exfiltration from various sources, such as

endpoints, networks, cloud services, or email. DLP tools can also enforce data protection policies and

compliance requirements, such as encryption, masking, or deletion of sensitive data. DLP tools can

help to protect personal data from both internal and external threats, such as malicious insiders,

hackers, or accidental exposure.

Reference:

Data protection solutions rely on technologies such as data loss prevention (DLP), storage with built-

in data protection, firewalls, encryption, and endpoint protection, Cloudian

Top 10 Hot Data Security And Privacy Technologies, Forbes

A third-party privacy control assessment is an independent and objective evaluation of the design

and effectiveness of the privacy controls implemented by an organization to protect personal data

and comply with privacy laws and regulations. A third-party privacy control assessment can help

senior management to verify the success of its commitment to privacy by design, by providing the

following benefits:

It can measure the extent to which the organization has adopted and integrated the principles and

practices of privacy by design throughout its products, services, processes and systems.

It can identify the strengths and weaknesses of the organization’s privacy governance, policies,

procedures, standards and guidelines, and provide recommendations for improvement.

It can validate the organization’s compliance with the applicable privacy requirements and

expectations of its customers, stakeholders, regulators and auditors.

It can enhance the organization’s reputation and trustworthiness as a responsible and transparent

data controller and processor.

The other options are less effective or irrelevant for verifying the success of the commitment to

privacy by design. Reviewing the findings of an industry benchmarking assessment may provide

some insights into how the organization compares with its peers or competitors in terms of privacy

performance, but it may not reflect the specific privacy goals, risks and challenges of the

organization. Identifying trends in the organization’s amount of compromised personal data or

number of privacy incidents may indicate some aspects of the organization’s privacy maturity, but

they are reactive and lagging indicators that do not capture the proactive and preventive nature of

privacy by design. Moreover, these metrics may not account for other factors that may influence the

occurrence or impact of data breaches or privacy violations, such as external threats, human errors

or environmental changes.

Reference:

Privacy by Design: How Far Have We Come? - ISACA, section 1: “Privacy by design challenges

conventional system thinking. It mandates that any system, process or infrastructure that uses

personal data consider privacy throughout its development life cycle.”

Privacy Control Assessment - ISACA, section 1: “A Privacy Control Assessment (PCA) is an

independent evaluation performed by a qualified assessor to determine whether an entity’s controls

are suitably designed and operating effectively to meet its objectives related to protecting personal

information.”

Privacy by Design: The New Competitive Advantage - ISACA, section 2: “Privacy by design is a

proactive approach to embedding privacy into the design specifications of various technologies,

business practices and networked infrastructure.”

The best course of action to prevent false positives from data loss prevention (DLP) tools is to re-

establish baselines for configuration rules. False positives are events that are triggered by a DLP

policy in error, meaning that the policy has mistakenly identified non-sensitive data as sensitive or

blocked legitimate actions. False positives can reduce the effectiveness and efficiency of DLP tools by

generating unnecessary alerts, wasting resources, disrupting workflows, and creating user

frustration. To avoid false positives, DLP tools need to have accurate and updated configuration rules

that define what constitutes sensitive data and what actions are allowed or prohibited. Configuration

rules should be based on clear and consistent criteria, such as data classification levels, data sources,

data destinations, data formats, data patterns, user roles, user behaviors, etc. Configuration rules

should also be regularly reviewed and adjusted to reflect changes in business needs, regulatory

requirements, or threat landscape.

Conducting additional discovery scans, suppressing the alerts generating the false positives, or

evaluating new DLP tools are not the best ways to prevent false positives from DLP tools. Conducting

additional discovery scans may help identify more sensitive data in the network, but it does not

address the root cause of false positives, which is the misconfiguration of DLP policies. Suppressing

the alerts generating the false positives may reduce the noise and annoyance caused by false

positives, but it does not solve the problem of inaccurate or outdated DLP policies. Evaluating new

DLP tools may offer some advantages in terms of features or performance, but it does not guarantee

that false positives will be eliminated or reduced without proper configuration and tuning of DLP

policies.

Reference: False Positives Handling| Endpoint Data Loss Prevention - ManageEngine …, Scenario-

based troubleshooting guide - DLP Issues, Respond to a DLP policy violation in Power BI - Power BI

Reference: https://www.isaca.org/resources/isaca-journal/issues/2020/volume-4/incidentresponse-models

The primary objective of privacy incident response is to mitigate the impact of privacy incidents on

the organization and the data subjects. Privacy incident response is a process that involves

identifying, containing, analyzing, resolving, and learning from privacy incidents that involve

personal data. Privacy incident response aims to reduce the harm and liability that may result from

privacy incidents, such as reputational damage, regulatory fines, legal actions, or loss of trust. Privacy

incident response also helps to improve the organization’s privacy posture and resilience by

implementing corrective and preventive measures.

While notifying data subjects impacted by privacy incidents may be a legal or ethical obligation, it is

not the primary objective of privacy incident response. Rather, it is one of the possible steps or

outcomes of the process, depending on the nature and severity of the incident. Similarly, reducing

privacy risk to the lowest possible level or optimizing the costs associated with privacy incidents are

desirable goals, but not the main purpose of privacy incident response.

Reference: Privacy incidents and breaches, DHS Privacy Incident Handling Guidance, Incident and

Breach Management

Prioritizing privacy-related risk scenarios as part of ERM processes is the best way to ensure that the

risk responses meet the organizational objectives, because it helps to align the privacy risk

management with the overall strategic goals, values, and culture of the organization. ERM is a

holistic approach to identify, assess, and manage risks across the organization, taking into account

the interdependencies and trade-offs among different types of risks. By integrating privacy-related

risk scenarios into the ERM processes, the organization can evaluate the potential impact and

likelihood of privacy risks on its mission, vision, and performance, and prioritize the most significant

ones for mitigation or acceptance. This can also help to allocate appropriate resources, assign clear

roles and responsibilities, and monitor and report on the effectiveness of the risk responses.

Reference:

Privacy Risk Management, ISACA Journal

Enterprise Risk Assessment, Deloitte

Collecting only the data necessary to meet objectives is the best approach to minimize privacy risk

when collecting personal data. This is based on the principle of data minimization, which states that

personal data should be adequate, relevant, and limited to what is necessary in relation to the

purposes for which they are processed. Using a third party, collecting data through a secure web

server, or aggregating data immediately may reduce some privacy risks, but they do not eliminate

the possibility of collecting excessive or unnecessary data. Reference: CDPSE Exam Content Outline,

Domain 3, Task 3.2

After a privacy risk has been accepted, the next step is to monitor the risk landscape for material

changes. This means that the organization should keep track of any internal or external factors that

may affect the likelihood or impact of the risk, such as new threats, vulnerabilities, regulations,

technologies, or business processes. Monitoring the risk landscape can help the organization identify

if the risk acceptance decision is still valid, or if it needs to be revisited or revised. Monitoring can

also help the organization prepare for potential incidents or consequences that may arise from the

accepted risk.

Before an organization can respond to data subject access requests (DSARs), it needs to have a clear

understanding of the data in its possession, such as what types of personal data are collected, where

they are stored, how they are processed, who has access to them, and how long they are retained.

This will help the organization to locate and retrieve the relevant data for each DSAR, and to ensure

that the data are accurate, complete and up to date. Understanding the data in its possession will

also help the organization to comply with other data protection principles and obligations, such as

data minimization, purpose limitation, security and accountability.

The other options are less important or irrelevant to do first. Investing in a platform to automate data

review may help to speed up the response process, but it does not guarantee that the organization

has identified all the data sources and categories that are subject to DSARs. Confirming what is

required for disclosure is also important, but it depends on the specific request and the applicable

law or regulation. Creating a policy for handling access requests is a good practice, but it should be

based on a thorough understanding of the data in its possession.

Reference:

Practical Data Security and Privacy for GDPR and CCPA - ISACA, section 2: “It is important to

understand what personal information is collected and processed by an organization.”

Introduction to Data Subject Access Requests - Everlaw, section 3: “The first step in responding to a

DSAR is identifying where the relevant personal data reside within your organization.”

Guidelines 01/2022 on data subject rights - Right of access Version 1, section 2.1: “The controller

should have a clear overview of all processing activities involving personal data.”

Application hardening measures are the most important action to protect a mobile banking app and

its data against manipulation and disclosure because they prevent attackers from reverse

engineering, tampering, or injecting malicious code into the app. Application hardening measures

include techniques such as code obfuscation, encryption, integrity checks, anti-debugging, and anti-

tampering mechanisms. These measures make the app more resilient and secure against various

types of cyberattacks.

Reference:

ISACA Certified Data Privacy Solutions Engineer Study Guide, Domain 3: Privacy Engineering, Task

3.4: Implement privacy engineering techniques to protect data in applications and systems, p. 104-

105.

What is Application Hardening? | Glossary | Digital.ai

Conducting a risk assessment of all candidate vendors is the best way to provide assurance that a

potential vendor is able to comply with privacy regulations and the organization’s data privacy policy,

because it allows the organization to evaluate the vendor’s privacy practices, controls, and

performance against a set of criteria and standards. A risk assessment can also help to identify any

gaps, weaknesses, or threats that may pose a risk to the organization’s data privacy objectives and

obligations. A risk assessment can be based on various sources of information, such as self-

attestations, documentation, audits, or independent verification. A risk assessment can also help to

prioritize the vendors based on their level of risk and impact, and to determine the appropriate

mitigation or monitoring actions.

Reference:

8 Steps to Manage Vendor Data Privacy Compliance, DocuSign

Supplier Security and Privacy Assurance (SSPA) program, Microsoft Learn

A thin client remote desktop protocol (RDP) is the most effective remote access model for reducing

the likelihood of attacks originating from connecting devices, because it minimizes the amount of

data and processing that occurs on the remote device. A thin client RDP only sends keyboard, mouse

and display information between the remote device and the server, while the actual processing and

storage of data happens on the server. This reduces the exposure of sensitive data and applications

to potential attackers who may compromise the remote device.

Reference:

CDPSE Review Manual, Chapter 2 – Privacy Architecture, Section 2.3 – Privacy Architecture

Implementation1.

CDPSE Certified Data Privacy Solutions Engineer All-in-One Exam Guide, Chapter 2 – Privacy

Architecture, Section 2.4 – Remote Access2.

The first step toward the effective management of personal data assets is to create a personal data

inventory, which is a comprehensive list of the personal data that an organization collects, processes,

stores, transfers, and disposes of. A personal data inventory helps an organization to understand the

types, sources, locations, owners, purposes, and retention periods of the personal data it holds, as

well as the risks and obligations associated with them. A personal data inventory is essential for

complying with data privacy laws and regulations, such as the GDPR or the PDPA, which require

organizations to implement data protection principles and practices, such as obtaining consent,

providing notice, ensuring data quality and security, respecting data subject rights, and reporting

data breaches. A personal data inventory also helps an organization to identify and mitigate data

privacy risks and gaps, and to implement data minimization and data security controls.

Reference:

ISACA, Data Privacy Audit/Assurance Program, Control Objective 3: Data Inventory and

Classification1

ISACA, Simplify and Contextualize Your Data Classification Efforts2

PDPC, Managing Personal Data3

PDPC, PDPA Assessment Tool for Organisations4

In GDPR parlance, organizations that use third-party service providers are often, but not always,

considered data controllers, which are entities that determine the purposes and means of the

processing of personal data, which can include directing third parties to process personal data on

their behalf. The third parties that process data for data controllers are known as data processors.

The best way to protect personal data in the custody of a third party is to include requirements to

comply with the organization’s privacy policies in the contract. This means that the organization

should specify the terms and conditions of data processing, such as the purpose, scope, duration,

and security measures, and ensure that they are consistent with the organization’s privacy policies

and applicable privacy regulations. The contract should also define the roles and responsibilities of

both parties, such as data controller and data processor, and establish mechanisms for monitoring,

reporting, auditing, and resolving any issues or incidents related to data privacy. Reference: : CDPSE

Review Manual (Digital Version), page 41

The first thing that an IT privacy practitioner should do before an organization migrates personal data

from an on-premise solution to a cloud-hosted solution is to perform a privacy impact assessment

(PIA). A 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 measures to protect

personal data in a cloud-hosted solution, such as encryption, pseudonymization, anonymization,

access control, audit trail, breach notification, etc. A PIA also helps to comply with the applicable

privacy regulations and standards that govern data processing activities in a cloud-hosted

solution. Reference: : CDPSE Review Manual (Digital Version), page 99