Free Practice Questions for Isaca CDPSE Exam

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?

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

The greatest benefit of adopting data minimization practices is that the associated threat surface is reduced. Data minimization is a privacy principle that states that personal data should be adequate, relevant, and limited to what is necessary for the purposes for which they are processed. Data minimization helps to protect data privacy by reducing the amount and type of personal data that are collected, stored, processed, or shared by an organization. This in turn reduces the exposure of personal data to potential threats, such as unauthorized access, use, disclosure, modification, or loss. References: : CDPSE Review Manual (Digital Version), page 29

Encryption is a security practice that transforms data into an unreadable format using a secret key or algorithm. Encryption protects the confidentiality and integrity of data, especially when they are transferred using email or other communication channels. Encryption ensures that only authorized parties can access and use the data, while unauthorized parties cannot decipher or modify the data without the key or algorithm. Encryption also helps to comply with data protection laws and regulations, such as the General Data Protection Regulation (GDPR) or the California Consumer Privacy Act (CCPA), which require data controllers and processors to implement appropriate technical and organizational measures to safeguard personal data.

Centrally managed encryption is a type of encryption that is implemented and controlled by a central authority or system, such as an organization or a service provider. Centrally managed encryption has the following advantages over end user-managed encryption, private cloud storage space, or password-protected .zip files, for reducing the risk of compromise when transferring personal information using email:

It can enforce consistent and standardized encryption policies and procedures across the organization or the service, such as the encryption standards, algorithms, keys, modes, and formats.

It can automate the encryption and decryption processes for the users, without requiring them to perform any manual actions or install any software or plug-ins on their devices.

It can monitor and audit the encryption activities and incidents, and provide visibility and accountability for the data protection and compliance status.

It can reduce the human errors or negligence that may compromise the encryption security, such as losing or sharing the keys, forgetting or reusing the passwords, or sending the data to the wrong recipients.

References:

Encryption in the Hands of End Users - ISACA, section 2: “A key goal of encryption is to protect the file even when direct access is possible or the transfer is intercepted.”

The Complexity Conundrum: Simplifying Data Security - ISACA, section 3: “Centrally managed encryption solutions can help enterprises overcome these challenges by providing a unified platform for encrypting data across different environments and applications.”

Email Encryption: What You Need to Know - Lifewire, section 1: “Email encryption is a way of protecting your email messages from being read by anyone other than the intended recipients.”

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. References: 1 Domain 2, Task 7

Requirements definition is a phase of the software development life cycle (SDLC) that involves gathering, analyzing and documenting the functional and non-functional requirements of the software system or application, such as features, performance, security and usability. It is most important to consider privacy by design principles during this phase, as it would help to ensure that privacy is embedded and integrated into the software system or application from the outset, rather than as an afterthought or an add-on. Considering privacy by design principles during requirements definition would also help to avoid costly rework or delays later in the SDLC, as well as to enhance customer trust and satisfaction, and comply with privacy laws and regulations. The other options are not as important as requirements definition in considering privacy by design principles. Application design is a phase of the SDLC that involves creating and specifying the architecture, components, interfaces and data models of the software system or application, based on the requirements defined in the previous phase. Implementation is a phase of the SDLC that involves coding, testing and debugging the software system or application, based on the design specifications created in the previous phase. Testing is a phase of the SDLC that involves verifying and validating that the software system or application meets the requirements and expectations of the users and stakeholders, as well as identifying and fixing any defects or errors1, p. 88-89 References: 1: CDPSE Review Manual (Digital Version)

A raw zone is a zone within a data lake that contains unprocessed or unstructured data that is ingested from various sources without any transformation or validation. A raw zone may contain sensitive data that has not been identified or classified yet, such as personal data. Therefore, sensitive data in a raw zone should be encrypted or tokenized to protect its confidentiality and integrity. Encryption is a process of transforming data into an unreadable form using a secret key or algorithm. Tokenization is a process of replacing sensitive data with non-sensitive substitutes called tokens. Both encryption and tokenization help to prevent unauthorized or unlawful access, use, disclosure, or transfer of sensitive data in a raw zone. References: : CDPSE Review Manual (Digital Version), page 169

The primary reason to complete a privacy impact assessment (PIA) is to understand privacy risks associated with the collection, use, disclosure or retention of personal data. A PIA is a systematic process to identify and evaluate the potential privacy impacts of a system, project, program or initiative that involves personal data processing activities. A PIA helps to ensure that privacy risks are identified and mitigated before the implementation is executed. A PIA also helps to ensure compliance with privacy principles, laws and regulations, and alignment with customer expectations and preferences. The other options are not primary reasons to complete a PIA. To comply with consumer regulatory requirements may be a reason to complete a PIA, but it is not the primary reason, as consumer regulatory requirements may vary depending on the context and jurisdiction. To establish privacy breach response procedures may be an outcome of completing a PIA, but it is not the primary reason, as privacy breach response procedures are only one aspect of mitigating privacy risks. To classify personal data may be an activity that is part of completing a PIA, but it is not the primary reason, as personal data classification is only one aspect of understanding privacy risks1, p. 67 References: 1: CDPSE Review Manual (Digital Version)

The best answer is D. Assess the organization’s exposure related to the migration.

A comprehensive explanation is:

Before an organization migrates data from an on-premise solution to a cloud-hosted solution that spans more than one jurisdiction, it should first assess its exposure related to the migration. This means that the organization should identify and evaluate the potential risks and benefits of moving its data to the cloud, taking into account the legal, regulatory, contractual, and ethical obligations and implications of doing so.

Some of the factors that the organization should consider in its assessment are:

The nature, sensitivity, and value of the data being migrated, and the impact of its loss, theft, corruption, or disclosure on the organization and its stakeholders.

The security, privacy, and compliance requirements and standards that apply to the data in each jurisdiction where it is stored, processed, or accessed, and the differences or conflicts among them.

The trustworthiness, reliability, and reputation of the cloud service provider and its subcontractors, and the terms and conditions of their service level agreements (SLAs) and contracts.

The availability, performance, scalability, and cost-effectiveness of the cloud-hosted solution compared to the on-premise solution, and the trade-offs involved.

The technical feasibility and complexity of migrating the data from the on-premise solution to the cloud-hosted solution, and the tools and methods needed to do so.

The organizational readiness and capability to manage the change and transition from the on-premise solution to the cloud-hosted solution, and the training and support needed for the staff and users.

By conducting a thorough assessment of its exposure related to the migration, the organization can make an informed decision about whether to proceed with the migration or not, or under what conditions or modifications. The assessment can also help the organization to plan and implement appropriate measures and controls to mitigate or avoid any negative consequences and enhance or maximize any positive outcomes of the migration.

Ensuring data loss prevention (DLP) alerts are turned on (A), encrypting the data while it is being migrated (B), and conducting a penetration test of the hosted solution © are all good practices to protect data privacy and security when migrating data from an on-premise solution to a cloud-hosted solution that spans more than one jurisdiction. However they are not the first steps that should be done before the migration. They are more relevant during or after the migration process. They also do not address other aspects of exposure related to the migration, such as legal, regulatory, contractual, or ethical issues.

References:

Data Migration: On-Premise to Cloud - 10 Steps to Success1

8 Best Practices for On-Premises to Cloud Migration2

5 Steps for a Successful On-Premise to Cloud Migration3

Extend on-premises data solutions to the cloud4

On Premise to Cloud migration tool5

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.

References:

Ensuring Data Integrity with Hash Codes, Microsoft Learn

What is ‘hashing,’ and does it help avoid the obligations imposed by the new privacy regulations?, Data Privacy Dish