CDPSE Exam Dumps - Isaca Certification Questions and Answers

The most useful information for prioritizing database selection for encryption is the asset classification scheme. An asset classification scheme is a system of organizing and categorizing assets based on their value, sensitivity, criticality, or risk level. An asset classification scheme helps to determine the appropriate level of protection or handling for each asset. For example, an asset classification scheme may assign labels such as public, internal, confidential, or secret to different types of data based on their impact if compromised. Databases that contain higher-classified data should be prioritized for encryption to prevent unauthorized access, disclosure, or modification.

Database administration audit logs, historical security incidents, or penetration test results are also useful information for database security, but they are not the most useful for prioritizing database selection for encryption. Database administration audit logs are records of activities performed by database administrators or other privileged users on the database system. Database administration audit logs help to monitor and verify the actions and changes made by authorized users and detect any anomalies or violations. Historical security incidents are records of events that have compromised or threatened the security of the database system in the past. Historical security incidents help to identify and analyze the root causes, impacts, and lessons learned from previous breaches or attacks. Penetration test results are reports of simulated attacks performed by ethical hackers or security experts on the database system to evaluate its vulnerabilities and defenses. Penetration test results help to discover and exploit any weaknesses or gaps in the database security posture and recommend remediation actions.

References: Data Classification Policy - SANS Institute, Database Security Best Practices - Oracle, [Database Security: An Essential Guide | IBM]

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 most effective way to incorporate privacy by design principles into applications is to include privacy requirements in software development practices, because this ensures that privacy is considered and integrated from the early stages of the design process and throughout the entire lifecycle of the application. Software development practices include activities such as defining the scope, objectives, and specifications of the application, identifying and analyzing the privacy risks and impacts, selecting and implementing the appropriate privacy-enhancing technologies and controls, testing and validating the privacy functionality and performance, and monitoring and reviewing the privacy compliance and effectiveness of the application. By including privacy requirements in software development practices, the organization can achieve a proactive, preventive, and embedded approach to privacy that aligns with the privacy by design principles.

References:

• CDPSE Review Manual, 2023 Edition, Domain 2: Privacy Architecture, Section 2.1.2: Privacy Requirements, p. 75
• CDPSE Review Manual, 2023 Edition, Domain 2: Privacy Architecture, Section 2.2.1: Privacy by Design Methodology, p. 79-80
• The 7 Principles of Privacy by Design | Blog | OneTrust1

The best way to validate compliance with agreed-upon service levels established with a third party that processes personal data is to have a contractual right to audit, which means that the organization can conduct audits or inspections of the third party’s privacy practices, policies, and procedures to verify that they meet the contractual obligations and expectations. A contractual right to audit can also help identify and address any privacy risks or gaps that may arise from the third party’s processing of personal data12.

References:

• CDPSE Exam Content Outline, Domain 1 – Privacy Governance (Governance, Management & Risk Management), Task 7: Participate in the management and evaluation of contracts, service levels and practices of vendors and other external parties3.
• CDPSE Review Manual, Chapter 1 – Privacy Governance, Section 1.4 – Third-Party Management4.

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

Code review is a primary element of application and software hardening. Code review is a process of examining the source code of an application or software to identify and fix errors, vulnerabilities, or inefficiencies that may compromise its functionality, security, or performance. Code review can help prevent common security risks such as buffer overflows, SQL injections, cross-site scripting, or logic flaws. Code review can also help improve the quality, readability, maintainability, and usability of the code. Code review can be done manually by developers or peers, or automatically by tools such as static code analyzers or code quality checkers.

Vulnerability analysis, database configuration, and software repository are also important for application and software hardening, but they are not primary elements. Vulnerability analysis is a process of identifying and assessing the weaknesses or flaws in an application or software that may expose it to attacks or exploitation. Vulnerability analysis can be done by tools such as vulnerability scanners or penetration testers. Database configuration is a process of setting up and managing the parameters, options, or features of a database system that stores or processes data for an application or software. Database configuration can include aspects such as access control, encryption, backup, recovery, performance tuning, or replication. Software repository is a location where the source code, binaries, or documentation of an application or software are stored and managed. Software repository can facilitate version control, collaboration, distribution, or deployment of the application or software.

References: What is Application Hardening ? - GeeksforGeeks, What is OS Hardening and How Can Developers Implement it, System Hardening: An Easy-to-Understand Overview - Trenton Systems

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

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 preferences 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.

References:

• 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.

A retention schedule is a document that specifies how long different types of records or data should be kept and when they should be deleted or disposed of, based on legal, regulatory, operational or historical requirements. A retention schedule is the best indication of an effective records management program for personal data, as it reflects the principles of data minimization and storage limitation, which require limiting the collection, storage and processing of personal data to what is necessary and relevant for the intended purposes, and deleting or disposing of personal data when it is no longer needed or justified. A retention schedule also helps to reduce the privacy risks and costs associated with data storage and retention, such as data breaches, unauthorized access, misuse or loss of data. The other options are not as indicative of an effective records management program for personal data as a retention schedule. Archived data is used for future analytics may indicate that the organization is leveraging its data assets for business intelligence or research purposes, but it may not comply with the principles of data minimization and storage limitation, or the privacy rights and preferences of the data subjects. The legal department has approved the retention policy may indicate that the organization has obtained legal advice or guidance on its records management program for personal data, but it may not reflect the actual implementation or execution of the retention policy. All sensitive data has been tagged may indicate that the organization has implemented a data classification scheme for its records or data, but it may not indicate how long the records or data should be kept or when they should be deleted or disposed of1, p. 99-100 References: 1: CDPSE Review Manual (Digital Version)