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ISACA Certified Data Privacy Solutions Engineer Sample Questions (Q46-Q51):
NEW QUESTION # 46
When configuring information systems for the communication and transport of personal data, an organization should:
- A. review configuration settings for compliance.
- B. enable essential capabilities only.
- C. implement the least restrictive mode.
- D. adopt the default vendor specifications.
Answer: A
Explanation:
Reference:
When configuring information systems for the communication and transport of personal data, an organization should review configuration settings for compliance with privacy regulations and standards. This means that the organization should ensure that the configuration settings are aligned with the privacy principles and requirements that apply to the data being communicated or transported, such as data minimization, purpose limitation, consent, encryption, pseudonymization, anonymization, etc. The organization should also document and monitor the configuration settings and perform regular audits and reviews to verify their effectiveness and compliance. Reference: : CDPSE Review Manual (Digital Version), page 151
NEW QUESTION # 47
Which of the following helps define data retention time is a stream-fed data lake that includes personal data?
- A. Data privacy standards
- B. Information security assessments
- C. Privacy impact assessments (PIAs)
- D. Data lake configuration
Answer: C
Explanation:
Explanation
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
NEW QUESTION # 48
Which of the following is an example of data anonymization as a means to protect personal data when sharing a database?
- A. The data is encrypted and a key is required to re-identify the data.
- B. Key fields are hidden and unmasking is required to access to the data.
- C. The data is transformed such that re-identification is impossible.
- D. Names and addresses are removed but the rest of the data is left untouched.
Answer: C
Explanation:
Explanation
Data anonymization is a method of protecting personal data by modifying or removing any information that can be used to identify an individual, either directly or indirectly, in a data set. Data anonymization aims to prevent the re-identification of the data subjects, even by the data controller or processor, or by using additional data sources or techniques. Data anonymization 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 respect the privacy rights and preferences of the data subjects.
The data is transformed such that re-identification is impossible is an example of data anonymization, as it involves applying irreversible techniques, such as aggregation, generalization, perturbation, or synthesis, to alter the original data in a way that preserves their utility and meaning, but eliminates their identifiability. For example, a database of customer transactions can be anonymized by replacing the names and addresses of the customers with random codes, and by adding noise or rounding to the amounts and dates of the transactions.
The other options are not examples of data anonymization, but of other methods of protecting personal data that do not guarantee the impossibility of re-identification. The data is encrypted and a key is required to re-identify the data is an example of data pseudonymization, which is a method of replacing direct identifiers with pseudonyms, such as codes or tokens, that can be linked back to the original data with a key or algorithm.
Data pseudonymization does not prevent re-identification by authorized parties who have access to the key or algorithm, or by unauthorized parties who can break or bypass the encryption. Key fields are hidden and unmasking is required to access to the data is an example of data masking, which is a method of concealing or obscuring sensitive data elements, such as names or credit card numbers, with characters, symbols or blanks.
Data masking does not prevent re-identification by authorized parties who have permission to unmask the data, or by unauthorized parties who can infer or guess the hidden data from other sources or clues. Names and addresses are removed but the rest of the data is left untouched is an example of data deletion, which is a method of removing direct identifiers from a data set. Data deletion does not prevent re-identification by using indirect identifiers, such as age, gender, occupation or location, that can be combined or matched with other data sources to re-establish the identity of the data subjects.
References:
Big Data Deidentification, Reidentification and Anonymization - ISACA, section 2: "Anonymization is the ability for the data controller to anonymize the data in a way that it is impossible for anyone to establish the identity of the data." Data Anonymization - Overview, Techniques, Advantages, section 1: "Data anonymization is a method of ensuring that the company understands and enforces its duty to secure sensitive, personal, and confidential data in a world of highly complex data protection mandates that can vary depending on where the business and the customers are based."
NEW QUESTION # 49
Within a business continuity plan (BCP), which of the following is the MOST important consideration to ensure the ability to restore availability and access to personal data in the event of a data privacy incident?
- A. Recovery time objective (RTO)
- B. Online backup frequency
- C. Recovery point objective (RPO)
- D. Offline backup availability
Answer: C
Explanation:
Reference:
Recovery point objective (RPO) is the maximum amount of data that can be lost or corrupted before it affects the ability to restore the normal operations of a business. RPO is measured by the time interval between the last valid backup and the occurrence of a data privacy incident. A lower RPO means less data loss and faster recovery, while a higher RPO means more data loss and slower recovery. Therefore, RPO is the most important consideration to ensure the ability to restore availability and access to personal data in the event of a data privacy incident, because it determines how frequently and thoroughly the personal data should be backed up and protected.
IT Disaster Recovery Plan, Ready.gov
Understanding data backup, recovery, and business continuity, Leverage ITC Business Continuity & Disaster Recovery Planning (BCP & DRP), Imperva
NEW QUESTION # 50
Which of the following scenarios should trigger the completion of a privacy impact assessment (PIA)?
- A. New inter-organizational data flows
- B. Updates to data quality standards
- C. New data retention and backup policies
- D. Updates to the enterprise data policy
Answer: A
Explanation:
Explanation
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?
NEW QUESTION # 51
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