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Awareness campaigns are initiatives that aim to educate and inform employees about the importance of privacy protection, the organization’s privacy policies and procedures, the applicable laws and regulations, and the best practices and behaviors to safeguard personal data. Awareness campaigns can support an organization’s efforts to create and maintain desired privacy protection practices among employees by raising their awareness, understanding and commitment to privacy, as well as by influencing their attitudes, values and culture. Awareness campaigns can use various methods and channels, such as posters, newsletters, videos, webinars, quizzes, games or events, to deliver consistent and engaging messages to the target audience. The other options are not the best ways to support an organization’s efforts to create and maintain desired privacy protection practices among employees. Skills training programs are focused on developing specific technical or functional skills related to privacy, but they may not address the broader aspects of privacy awareness or culture. Performance evaluations are focused on measuring and rewarding individual or team performance based on predefined criteria or objectives, but they may not reflect the actual level of privacy awareness or practice. Code of conduct principles are focused on establishing and enforcing ethical standards and rules of behavior for employees, but they may not be sufficient to create or maintain privacy awareness or practice without effective communication and education1, p. 103-104 References: 1: CDPSE Review Manual (Digital Version)

User behavior analytics is a technology that uses data analysis and machine learning to monitor, detect and respond to anomalous or malicious user activities, such as accessing sensitive personal customer information to use for unauthorized purposes. User behavior analytics is the best choice to mitigate this risk, as it would help to identify and prevent insider threats, data breaches, fraud or misuse of data by authorized individuals. User behavior analytics can also help to enforce policies and controls, such as access control, audit trail or data loss prevention. The other options are not as effective as user behavior analytics in mitigating this risk. Email filtering system is a technology that scans and blocks incoming or outgoing emails that contain spam, malware or phishing attempts, but it does not address the issue of authorized individuals accessing sensitive personal customer information to use for unauthorized purposes. Intrusion monitoring is a technology that monitors and alerts on unauthorized or malicious attempts to access a system or network, but it does not address the issue of authorized individuals accessing sensitive personal customer information to use for unauthorized purposes. Mobile device management (MDM) is a technology that manages and secures mobile devices that are used to access or store organizational data, but it does not address the issue of authorized individuals accessing sensitive personal customer information to use for unauthorized purposes1, p. 92 References: 1: CDPSE Review Manual (Digital Version)

The first step when performing a data quality assessment is to assess the completeness of the data inventory, which is a comprehensive list of all data assets within the organization. This will help identify the scope, sources, owners, and characteristics of the data to be assessed. The other options are possible actions that may be taken after the data inventory is complete, depending on the objectives and criteria of the assessment.

References:

• CDPSE Exam Content Outline, Domain 3 – Data Lifecycle (Data Quality), Task 1: Perform a data quality assessment1.
• CDPSE Review Manual, Chapter 3 – Data Lifecycle, Section 3.2 – Data Quality2.

Endpoint encryption is a security practice that transforms the data stored on a laptop or other device into an unreadable format using a secret key or algorithm. Endpoint encryption protects the privacy of data in case of loss or theft, by ensuring that only authorized parties can access and use the data, while unauthorized parties cannot decipher or modify the data without the key or algorithm. Endpoint 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.

The other options are less effective or irrelevant for protecting the privacy of data stored on a laptop in case of loss or theft. Strong authentication controls, such as passwords, biometrics or multifactor authentication, are important for verifying the identity and access rights of users, but they do not protect the data from being accessed by bypassing or breaking the authentication mechanisms. Remote wipe is a feature that allows users or administrators to erase the data on a lost or stolen device remotely, but it depends on the availability of network connection and device power, and it may not prevent data recovery by sophisticated tools. Regular backups are a process of creating copies of data for recovery purposes, such as in case of data loss or corruption, but they do not protect the data from being accessed by unauthorized parties who may obtain the backup media or files.

References:

• An Ethical Approach to Data Privacy Protection - ISACA, section 2: “Encryption is one of the most effective security controls available to enterprises, but it can be challenging to deploy and maintain across a complex enterprise landscape.”
• How to Protect and Secure Your Data in 10 Ways - TechRepublic, section 1: “Encrypt your hard drive Most work laptops use BitLocker to encrypt local files. That way, if the computer is stolen or hacked, the data it contains will be useless to the malicious actor.”
• 10 Tips to Protect Your Files on PC and Cloud - microsoft.com, section 1: “Encrypt your hard drive Most work laptops use BitLocker to encrypt local files. That way, if the computer is stolen or hacked, the data it contains will be useless to the malicious actor.”
• 11 practical ways to keep your IT systems safe and secure | ICO, section 1: “Use strong passwords and multi-factor authentication Make sure you use strong passwords on smartphones, laptops, tablets, email accounts and any other devices or accounts where personal information is stored.”

Privacy by design is an approach that embeds privacy principles and considerations into the design and development of products, services, systems, and processes that involve personal data. Privacy by design aims to protect the privacy and security of the data subjects, as well as to comply with the applicable privacy laws and regulations. One of the key principles of privacy by design is to obtain the consent and choice of the data subjects regarding the collection, use, and disclosure of their personal data. Therefore, the best example of privacy by design in the development of a consumer mobile application is to require consent before sharing locations, as this gives the data subjects control and transparency over their personal data. The other options are not as effective or sufficient as requiring consent before sharing locations, as they do not address the principle of consent and choice, or they may violate other privacy principles or requirements.

References: CDPSE Review Manual, 2021, p. 35

The primary reason that a single cryptographic key should be used for only one purpose, such as encryption or authentication, is that it minimizes the risk if the cryptographic key is compromised. A cryptographic key is a piece of information that is used to perform cryptographic operations, such as encryption or authentication. Encryption is a process of transforming data into an unreadable form using a secret key or algorithm. Authentication is a process of verifying the identity or integrity of a user or data using a secret key or algorithm. If a single cryptographic key is used for multiple purposes, such as encryption and authentication, it increases the risk if the cryptographic key is compromised. For example, if an attacker obtains the cryptographic key that is used for both encryption and authentication, they can decrypt and access personal data, as well as impersonate or modify legitimate users or data. Therefore, a single cryptographic key should be used for only one purpose, and different keys should be used for different purposes. References: : CDPSE Review Manual (Digital Version), page 107

The most important thing to consider when managing changes to the provision of services by a third party that processes personal data is the business impact due to the changes. Changes to the provision of services by a third party can affect the organization’s ability to meet its business objectives and legal obligations related to data processing activities. For example, changes to the service level agreement (SLA), the scope of services, the security measures, the location of servers, etc., can have implications for the quality, availability, confidentiality, integrity, and compliance of personal data processing. Therefore, an IT privacy practitioner should assess and evaluate the business impact due to the changes, and ensure that they are aligned with the organization’s privacy policies and applicable privacy regulations and standards. References: : CDPSE Review Manual (Digital Version), page 41

Biometric records are personal information that can be used to identify an individual based on their physical or behavioral characteristics, such as fingerprints, facial recognition, iris scans, voice patterns, etc. Biometric records are considered sensitive personal information that require special protection and consent from the data subject. Biometric records can be used for various purposes, such as authentication, identification, security, etc., but they also pose privacy risks, such as unauthorized access, use, disclosure, or transfer of biometric data. References: : CDPSE Review Manual (Digital Version), page 25

Online behavioral tracking is a tracking technology associated with unsolicited targeted advertisements that presents the greatest privacy risk. Online behavioral tracking is a technique that collects and analyzes personal data about users’ online activities, preferences, interests, and behaviors across different websites or platforms. Online behavioral tracking is used to create user profiles and deliver personalized or targeted advertisements that match users’ needs or wants. Online behavioral tracking poses a privacy risk because it can invade users’ privacy by collecting sensitive or intimate personal data without their knowledge or consent, such as health conditions, political views, sexual orientation, etc. Online behavioral tracking can also expose users to unwanted or inappropriate advertisements that may influence their decisions or actions. References: : CDPSE Review Manual (Digital Version), page 139

The primary means by which an organization communicates customer rights as it relates to the use of their personal information is publishing a privacy notice. A privacy notice is a document that informs the customers about how their personal information is collected, used, shared, stored, and protected by the organization, as well as what rights they have regarding their personal information, such as access, rectification, erasure, portability, objection, etc. A privacy notice should be clear, concise, transparent, and easily accessible to the customers, and should comply with the applicable privacy regulations and standards. A privacy notice helps to establish trust and transparency between the organization and the customers, and enables the customers to exercise their rights and choices over their personal information. References: : CDPSE Review Manual (Digital Version), page 39

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.

References:

• 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)

Asymmetric encryption is a method of encrypting and decrypting data using two different keys: a public key and a private key. The public key can be shared with anyone, while the private key is kept secret by the owner. Data encrypted with the public key can only be decrypted with the private key, and vice versa. Asymmetric encryption ensures the security of encryption keys when transferring data containing personal information between cloud applications, by providing the following benefits:

• It can prevent unauthorized access or use of the data, as only the intended recipient who has the matching private key can decrypt the data sent by the sender who has the public key.
• It can prevent man-in-the-middle attacks, where an attacker intercepts and modifies the data or keys in transit, as any tampering with the data or keys will result in decryption failure or error.
• It can enable digital signatures, where the sender encrypts a message digest of the data with their private key, and the recipient verifies it with the sender’s public key. Digital signatures can ensure the authenticity and integrity of the data and the sender.

The other options are less effective or irrelevant for ensuring the security of encryption keys when transferring data containing personal information between cloud applications. Whole disk encryption is a method of encrypting all the data on a disk or device, such as a laptop or a smartphone. It does not protect the data when they are transferred over a network or stored on a cloud server. Symmetric encryption is a method of encrypting and decrypting data using the same key. It requires both parties to securely exchange and store the key, which may be difficult or risky in a cloud environment. Digital signature is not a method of encryption, but an application of asymmetric encryption that can provide additional security features for data transmission.

Input validation controls are the best way to ensure consumer credit card numbers are accurately captured. Input validation controls are methods that check the format, type, range, and length of the input data before accepting, processing, or storing it. Input validation controls can help prevent errors, fraud, or data loss by rejecting invalid, incomplete, or malicious input. For example, input validation controls can verify that a credit card number follows the Luhn algorithm1, has the correct number of digits2, and matches the card issuer’s prefix3. Input validation controls can also prevent SQL injection attacks4 or cross-site scripting attacks5 that may compromise the security and privacy of the data.

Input reference controls, access controls, and reconciliation controls are also important for data quality and security, but they do not directly ensure the accuracy of consumer credit card numbers. Input reference controls are methods that compare the input data with a predefined list of values or a reference table to ensure consistency and validity. For example, input reference controls can check if a country name or a postal code is valid by looking up a database of valid values. Access controls are methods that restrict who can access, modify, or delete the data based on their roles, permissions, or credentials. For example, access controls can prevent unauthorized users from accessing or tampering with consumer credit card numbers. Reconciliation controls are methods that compare the data from different sources or systems to ensure completeness and accuracy. For example, reconciliation controls can check if the transactions recorded in the accounting system match the transactions processed by the payment gateway.

References: Luhn algorithm, Credit card number, Bank card number, SQL injection, Cross-site scripting

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.

References:

• 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 need-to-know basis principle is a security principle that states that access to personal data should be limited to those who have a legitimate purpose for accessing it. The need-to-know basis principle helps to protect data privacy by minimizing the exposure of personal data to unauthorized or unnecessary parties, reducing the risk of data breaches, leaks, or misuse. The need-to-know basis principle should be applied when designing a role-based user access model for a new application, by defining clear roles and responsibilities for different users, granting access rights based on their roles and functions, and enforcing access controls and audits to monitor and verify data access. References: : CDPSE Review Manual (Digital Version), page 105

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. References: : CDPSE Review Manual (Digital Version), page 41

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.

References:

• 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.

A data loss prevention (DLP) tool is a software solution that monitors, detects and prevents the unauthorized transmission or leakage of sensitive data, such as personal data, from an organization’s network or devices. A DLP tool can help to ensure the effectiveness of a policy requiring the encryption of personal data if transmitted through email, by applying the following controls:

• Scanning the content and attachments of outgoing emails for personal data, such as names, email addresses, biometric data, IP addresses, etc.
• Blocking or quarantining emails that contain unencrypted personal data, and alerting the sender and/or the administrator of the policy violation.
• Encrypting personal data automatically before sending them through email, using encryption standards and algorithms that are compliant with data protection laws and regulations, such as the General Data Protection Regulation (GDPR) or the California Consumer Privacy Act (CCPA).
• Generating audit logs and reports of email activities and incidents involving personal data, and providing visibility and accountability for policy compliance.

The other options are less effective or irrelevant to ensure the effectiveness of the policy. Providing periodic user awareness training on data encryption is a good practice, but it does not guarantee that users will follow the policy or know how to encrypt personal data properly. Conducting regular control self-assessments (CSAs) is a useful method to evaluate the design and operation of the policy, but it does not prevent or detect policy violations in real time. Enforcing annual attestation to policy compliance is a formal way to demonstrate user commitment to the policy, but it does not verify or measure the actual level of compliance.

References:

• The Complexity Conundrum: Simplifying Data Security - ISACA, section 3: “Data loss prevention (DLP) solutions can help prevent unauthorized access to sensitive information by monitoring network traffic for specific keywords or patterns.”
• Guide to Securing Personal Data in Electronic Medium, section 3.2: “Organisations should consider implementing DLP solutions to prevent unauthorised disclosure of personal data via email.”
• 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.”

A data use policy is a document that defines the rules and guidelines for how personal data are collected, used, stored, shared and deleted by an organization. It is an important part of data governance and compliance, as it helps to ensure that personal data are handled in a lawful, fair and transparent manner, respecting the rights and preferences of data subjects. A data use policy should include the requirements for collecting and using personal data, such as the legal basis, the purpose, the scope, the consent, the data minimization, the accuracy, the security and the accountability. These requirements help to establish the legitimacy and necessity of data processing activities, and to prevent unauthorized or excessive use of personal data.

References:

• ISACA Privacy Notice & Usage Disclosures, section 2.1: “We collect Personal Information from you when you provide it to us directly or through a third party who has assured us that they have obtained your consent.”
• Chapter Privacy Policy - Singapore Chapter - ISACA, section 2: “We will collect your personal data in accordance with the PDPA either directly from you or your authorized representatives, and/or through our third party service providers.”
• Data Minimization—A Practical Approach - ISACA, section 2: “Enterprises may only collect as much data as are necessary for the purposes defined at the time of collection, which may also be set out in a privacy notice (sometimes referred to as a privacy statement, a fair processing statement or a privacy policy).”
• Establishing Enterprise Roles for Data Protection - ISACA, section 3: “Data governance is typically implemented in organizations through policies, guidelines, tools and access controls.”

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.

The notice provided to customers during data collection is the most important consideration when determining retention periods for personal data, as it reflects the transparency and accountability principles of privacy and the expectations and preferences of the data subjects. The notice should inform the customers about the purposes and legal bases of the data processing, the rights and choices of the customers, and the safeguards and measures to protect the data, including how long the data will be kept and when it will be deleted or disposed of. The notice should also be consistent with the applicable laws and regulations that may prescribe or limit the retention periods for certain types of personal data. The other options are not as important as the notice provided to customers during data collection when determining retention periods for personal data. Sectoral best practices for the industry may provide some guidance or benchmarks for retention periods, but they may not reflect the specific context or needs of the organization or the customers. Data classification standards may help to categorize data according to its sensitivity and value, but they may not indicate how long the data should be retained or deleted. Storage capacity available for retained data may affect the feasibility or cost of retaining data, but it should not determine or override the retention periods based on privacy principles, laws or customer expectations1, p. 99-100 References: 1: CDPSE Review Manual (Digital Version)

The best way to address the concern that data collected by a third-party vendor and provided back to the organization may not be protected according to the organization’s privacy notice is to validate contract compliance. This means that the organization should verify that the third-party vendor is adhering to the terms and conditions of the contract, which should include clauses on data protection, privacy, and security. The contract should also specify the obligations and responsibilities of both parties regarding data collection, processing, storage, transfer, retention, and disposal. By validating contract compliance, the organization can ensure that the third-party vendor is following the same privacy standards and practices as the organization.

References:

• ISACA, CDPSE Review Manual 2021, Chapter 2: Privacy Governance, Section 2.3: Third-Party Management, p. 51-52.
• ISACA, Data Privacy Audit/Assurance Program, Control Objective 8: Third-Party Management, p. 14-151

Data sanitization is a process of permanently erasing or destroying data from a storage device or media to prevent unauthorized access or recovery of the data. Data sanitization methods can include physical destruction, degaussing, overwriting, encryption or cryptographic erasure. The most important consideration when using advanced data sanitization methods to ensure privacy data will be unrecoverable is the type of media on which the data is stored, as different media types may require different methods or techniques to achieve effective sanitization. For example, physical destruction may be suitable for optical disks or tapes, but not for solid state drives (SSDs) or flash memory devices. Degaussing may be effective for magnetic disks or tapes, but not for optical disks or SSDs. Overwriting may work for hard disk drives (HDDs) or SSDs, but not for tapes or optical disks. Encryption or cryptographic erasure may be applicable for any media type, but may require additional security measures to protect the encryption keys or certificates. The other options are not as important as the type of media when using advanced data sanitization methods. Subject matter expertise may be helpful, but not essential, as long as the appropriate method is selected and applied correctly. Regulatory compliance requirements may influence the choice of method, but not necessarily determine it, as different methods may meet different standards or criteria. Location of data may affect the feasibility or cost of applying a method, but not its effectiveness or suitability., p. 93-94 References: : CDPSE Review Manual (Digital Version)

Data masking is the process of hiding original data with modified content to protect sensitive data from unauthorized access or disclosure. Data masking is often used for testing purposes in non-production environments, where personal data is not needed or allowed. However, data masking can pose several challenges, especially for a global financial institution that has multiple interconnected systems and applications. One of the greatest challenges is to preserve the complex relationships within and across systems while masking the data. This means that the masked data must maintain the same format, referential integrity, semantic integrity, and uniqueness as the original data, so that the testing results are valid and reliable. For example, if a customer’s name is masked in one system, it must be masked consistently in all other systems that reference it. If a transaction amount is masked in one system, it must not violate any business rules or constraints in another system. If a credit card number is masked in one system, it must still be a valid credit card number in another system. Preserving these complex relationships can be challenging because it requires a thorough understanding of the data model, the business logic, and the dependencies among systems. It also requires a robust and flexible data masking tool that can handle different types of data and platforms.

The best way for an organization to ensure its vendors are complying with data privacy requirements defined in their contracts is to obtain independent assessments of the vendors’ data management processes, because this will provide an objective and reliable evaluation of the vendors’ privacy practices, policies, and controls. Independent assessments can be performed by external auditors, consultants, or certification bodies that have the expertise and credibility to verify the vendors’ compliance with the contractual obligations and expectations. Independent assessments can also help identify and address any privacy risks or gaps that may arise from the vendors’ 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.

Attribute-based access control (ABAC) is the best approach for limiting the access of regional HR team members to employee data only within their regional office, because it allows for fine-grained and dynamic access control based on attributes of the subject, object, environment, and action. Attributes are characteristics or properties that can be used to describe or identify entities, such as users, resources, locations, roles, or permissions. ABAC uses policies and rules that evaluate the attributes and grant or deny access accordingly. For example, an ABAC policy could state that a user can access an employee record if and only if the user’s role is HR and the user’s region matches the employee’s region. This way, the access control can be tailored to the specific needs and context of the organization, without relying on predefined or fixed access levels.

References:

• Attribute-Based Access Control (ABAC), NIST
• What is Attribute-Based Access Control (ABAC)?, Axiomatics
• Access Control Models – Westoahu Cybersecurity, Westoahu Cybersecurity

The primary consideration to ensure control of remote access is aligned to the privacy policy is that access is only granted to authorized users. This means that the organization should implement and enforce policies and procedures to identify, authenticate, and authorize users who need to access personal data remotely, such as employees, contractors, or service providers. The organization should also define and communicate the roles and responsibilities of remote users, and the terms and conditions of remote access, such as the purpose, scope, duration, and security measures. By granting access only to authorized users, the organization can protect data privacy by preventing unauthorized or unnecessary access, use, disclosure, or transfer of personal data. References: : CDPSE Review Manual (Digital Version), page 107

One of the most common vulnerabilities that can compromise the access to personal information is end users using weak passwords. Weak passwords are passwords that are easy to guess, crack, or steal, such as passwords that are short, simple, common, or reused. Weak passwords can allow unauthorized or malicious parties to gain access to personal information and cause privacy breaches, leaks, or misuse. Multi-factor authentication is an effective way to mitigate this vulnerability, as it requires end users to provide more than one piece of evidence to verify their identity, such as something they know (e.g., password), something they have (e.g., token), or something they are (e.g., biometric). Multi-factor authentication makes it harder for attackers to bypass the authentication process and access personal information. References: : CDPSE Review Manual (Digital Version), page 107

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 data protection principle that is applied when an online business posts its customer data protection notice that includes a statement indicating information is collected on how products are used, the content viewed, and the time and duration of online activities is lawfulness and fairness. Lawfulness and fairness are two of the core principles of data protection under various laws and regulations, such as the GDPR or the CCPA. They state that personal data should be processed lawfully, fairly and in a transparent manner in relation to the data subject. By posting a customer data protection notice that informs customers about what information is collected and for what purpose, the online business demonstrates its compliance with these principles.

System use requirements, data integrity and confidentiality, or data use limitation are not the correct names of the data protection principles that are applied in this case. System use requirements are not a specific principle of data protection, but rather a general term that refers to the rules or policies that govern how users can access and use a system or service. Data integrity and confidentiality are two aspects of the security principle of data protection, which states that personal data should be processed in a manner that ensures appropriate security of the personal data. Data use limitation is not a specific principle of data protection either, but rather a concept that relates to the purpose limitation principle, which states that personal data should be collected for specified, explicit and legitimate purposes and not further processed in a manner that is incompatible with those purposes.

References: A guide to the data protection principles | ICO, Data Protection Principles: Core Principles of the GDPR - Cloudian, Data Protection Basics: The 7 data protection principles

The best way to validate that privacy practices align to the published enterprise privacy management program is to conduct an audit. An audit is an independent and objective examination of evidence to provide assurance that privacy practices are effective and compliant with the enterprise privacy management program. An audit can also identify any gaps or weaknesses in the privacy practices and provide recommendations for improvement. An audit can be conducted internally or externally, depending on the scope, objectives, and standards of the audit. References: : CDPSE Review Manual (Digital Version), page 83

Transport Layer Security (TLS) is a protocol that provides secure communication over the internet by encrypting and authenticating data. TLS provides data integrity through the calculation of message digests, which are cryptographic hashes that summarize the content and structure of a message. The sender and the receiver of a message can compare the message digests to verify that the message has not been altered or corrupted during transmission. TLS also uses digital certificates, asymmetric encryption, and symmetric encryption to provide confidentiality and authentication, but these are not directly related to data integrity.

References: CDPSE Review Manual, 2021, p. 117

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

The most effective way to support organizational privacy awareness objectives is D. Customizing awareness training by business unit function.

A comprehensive explanation is:

Organizational privacy awareness objectives are the goals and expectations that an organization sets for its employees and stakeholders regarding the protection and management of personal data. Privacy awareness objectives may vary depending on the nature, scope, and purpose of the organization’s data processing activities, as well as the legal, regulatory, contractual, and ethical obligations and implications that apply to them.

One of the best practices to support organizational privacy awareness objectives is to customize awareness training by business unit function. This means that the organization should design and deliver privacy awareness training programs that are tailored to the specific roles, responsibilities, and needs of each business unit or department within the organization. Customizing awareness training by business unit function can have several benefits, such as:

• Enhancing the relevance and effectiveness of the training content and methods for each audience group, by addressing their specific privacy challenges, risks, and opportunities.
• Increasing the engagement and motivation of the trainees, by showing them how privacy relates to their daily tasks, goals, and performance.
• Improving the retention and application of the training knowledge and skills, by providing practical examples, scenarios, and exercises that reflect the real-world situations and problems that the trainees may encounter.
• Fostering a culture of privacy across the organization, by creating a common language and understanding of privacy concepts, principles, and practices among different business units or departments.

Some examples of how to customize awareness training by business unit function are:

• Providing different levels or modules of training based on the degree of access or exposure to personal data that each business unit or department has. For example, a basic level of training for all employees, an intermediate level of training for employees who handle personal data occasionally or incidentally, and an advanced level of training for employees who handle personal data regularly or extensively.
• Providing different topics or themes of training based on the type or category of personal data that each business unit or department processes. For example, a general topic of training for employees who process non-sensitive or non-personal data, a specific topic of training for employees who process sensitive or special data categories (such as health, biometric, financial, or political data), and a specialized topic of training for employees who process high-risk or high-value data (such as intellectual property, trade secrets, or customer loyalty data).
• Providing different formats or modes of training based on the preferences or constraints of each business unit or department. For example, a face-to-face format of training for employees who work in the same location or office, an online format of training for employees who work remotely or across different time zones, and a blended format of training for employees who work in a hybrid mode or have flexible schedules.

The other options are not as effective as option D.

Funding in-depth training and awareness education for data privacy staff (A) may improve the competence and confidence of the data privacy staff who are responsible for designing and implementing the privacy policies and practices of the organization, but it does not necessarily support the organizational privacy awareness objectives for the rest of the employees and stakeholders.

Implementing an annual training certification process (B) may ensure that the employees and stakeholders are updated and refreshed on the privacy policies and practices of the organization on a regular basis, but it does not necessarily address their specific privacy needs and challenges based on their business unit function.

Including mandatory awareness training as part of performance evaluations © may incentivize the employees and stakeholders to participate in and complete the privacy awareness training programs offered by the organization, but it does not necessarily enhance their understanding and application of privacy concepts and principles based on their business unit function.

References:

• The Benefits of Information Security and Privacy Awareness Training Programs1
• What Is Your Privacy and Data Protection Strategy?2
• What is Data Privacy Awareness?3

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.

References:

• Privacy Risk Management, ISACA Journal
• Enterprise Risk Assessment, Deloitte

The applicable privacy legislation needs to be identified first to define the privacy requirements to use when assessing the selection of IT systems, because it sets the legal obligations and standards for the organization to comply with when processing personal data. The type of data, the control frameworks, and the technology platforms are all dependent on the privacy legislation that applies to the organization and its data processing activities. Therefore, the privacy legislation is the primary source of privacy requirements for IT systems.

References:

• CDPSE Review Manual, 2023 Edition, Domain 2: Privacy Architecture, Section 2.1.2: Privacy Requirements, p. 75
• Compliance with Cybersecurity and Privacy Laws and Regulations1

A primary objective of performing a privacy impact assessment (PIA) prior to onboarding a new Software as a Service (SaaS) provider for a customer relationship management (CRM) system is to identify controls to mitigate data privacy risks, such as data breaches, unauthorized access, misuse or loss of data. A PIA would help to evaluate the potential privacy impacts of using a new SaaS provider for CRM data processing activities, such as collecting, storing, analyzing or transferring customer data, and to implement appropriate controls to mitigate those impacts, such as encryption, access control, backup, audit trail or contractual clauses. A PIA would also help to ensure compliance with privacy principles, laws and regulations, and alignment with customer expectations and preferences. The other options are not primary objectives of performing a PIA prior to onboarding a new SaaS provider for CRM data processing activities. Classifying personal data according to the data classification scheme is an activity that may be part of a PIA process, but it is not an objective in itself. Assessing the risk associated with personal data usage is an activity that may be part of a PIA process, but it is not an objective in itself. Determining the service provider’s ability to maintain data protection controls is an activity that may be part of a PIA process, but it is not an objective in itself1, p. 67 References: 1: CDPSE Review Manual (Digital Version)

A privacy impact assessment (PIA) is a systematic process to identify and evaluate the potential privacy impacts of a system, project, program or initiative that involves the collection, use, disclosure or retention of personal data. A PIA should be done first when planning a new implementation for tracking consumer web browser activity, as it would help to ensure that privacy risks are identified and mitigated before the implementation is executed. A PIA would also help to ensure compliance with privacy principles, laws and regulations, and alignment with consumer expectations and preferences. The other options are not as important as conducting a PIA when planning a new implementation for tracking consumer web browser activity. Seeking approval from regulatory authorities may be required or advisable for some types of personal data or data processing activities, but it may not be necessary or sufficient for tracking consumer web browser activity, depending on the context and jurisdiction. Obtaining consent from the organization’s clients may be required or advisable for some types of personal data or data processing activities, but it may not be necessary or sufficient for tracking consumer web browser activity, depending on the context and jurisdiction. Reviewing and updating the cookie policy may be required or advisable for some types of personal data or data processing activities, but it may not be necessary or sufficient for tracking consumer web browser activity, depending on the context and jurisdiction1, p. 67 References: 1: CDPSE Review Manual (Digital Version)

Validation and certification of data destruction is the most important consideration when choosing a method for data destruction, because it provides evidence that the data has been destroyed beyond recovery and that the organization has complied with the applicable information security frameworks and legal requirements. Validation and certification can also help to prevent data breaches, avoid legal liabilities, and enhance the organization’s reputation and trustworthiness. Different methods of data destruction may have different levels of validation and certification, depending on the type of media, the sensitivity of the data, and the standards and guidelines followed. For example, some methods may require a third-party verification or audit, while others may generate a certificate of destruction or a report of erasure. Therefore, the organization should choose a method that can provide sufficient validation and certification for its specific needs and obligations.

References:

• Secure Data Disposal and Destruction: 6 Methods to Follow, KirkpatrickPrice
• Data Destruction Standards and Guidelines, BitRaser
• Best Practices for Data Destruction, U.S. Department of Education

 Irreversible disposal is a process of removing or destroying data from a storage device or media to prevent unauthorized access or recovery of the data. Irreversible disposal is the most important thing to establish within a data storage policy to protect data privacy, 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. Irreversible disposal 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 important as irreversible disposal in protecting data privacy within a data storage policy. Data redaction is a technique that removes or obscures sensitive or confidential information from a document or file, but it does not address the issue of data retention or deletion. Data quality assurance (QA) is a process of ensuring that the data meets the standards and specifications of accuracy, completeness, consistency and reliability, but it does not address the issue of data retention or deletion. Collection limitation is a principle that requires limiting the collection of personal data to what is necessary and relevant for the intended purposes, but it does not address the issue of data retention or deletion1, p. 75-76 References: 1: CDPSE Review Manual (Digital Version)

The best way to ensure that application hardening is included throughout the software development life cycle (SDLC) is to include qualified application security personnel as part of the process. Application hardening is the process of applying security measures and techniques to an application to reduce its attack surface, vulnerabilities, and risks. Application hardening should be integrated into every stage of the SDLC, from planning and design to development and testing to deployment and maintenance. Including qualified application security personnel as part of the process helps to ensure that application hardening is performed effectively and consistently, as well as to provide guidance, feedback, and support to the developers, testers, and project managers. The other options are not as effective or sufficient as including qualified application security personnel as part of the process, as they do not address the root cause of the lack of application hardening, which is the gap in skills and knowledge among the SDLC participants.

References: CDPSE Review Manual, 2021, p. 131

One of the key principles of data protection is transparency, which means that individuals have the right to be informed about the collection and use of their personal data. This applies to video surveillance as well, especially in high security areas where the impact on privacy may be significant. Therefore, it is important to inform those affected by video surveillance about the purpose, scope, retention and access policies of the data collected.

References:

• ISACA Certified Data Privacy Solutions Engineer (CDPSE) Exam Content Outline, Domain 2: Privacy Architecture, Task 2.1: Design privacy controls based on privacy principles and legal requirements, Subtask 2.1.1: Identify applicable privacy principles and legal requirements.
• How can we comply with the data protection principles when using surveillance systems? | ICO

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]

Sectoral is a privacy protection reference model that refers to a system of laws and regulations that apply to specific sectors or industries within a jurisdiction, such as health, finance, education or telecommunications. Sectoral privacy protection is typically characterized by having different rules and standards for different types of personal data or data processing activities, depending on the sensitivity and value of the data or the impact and risk of the processing. When a government’s health division established the complete privacy regulation for only the health market, it is using a sectoral privacy protection reference model, as it is addressing the specific needs and challenges of the health sector in terms of privacy protection. The other options are not applicable in this scenario. Co-regulatory is a privacy protection reference model that refers to a system of laws and regulations that are supplemented by self-regulation mechanisms, such as codes of conduct, standards or certification schemes, developed by industry associations or professional bodies with oversight from government agencies or regulators. Comprehensive is a privacy protection reference model that refers to a system of laws and regulations that apply to all sectors and industries within a jurisdiction, regardless of the type or nature of personal data or data processing activities. Self-regulatory is a privacy protection reference model that refers to a system of laws and regulations that rely on voluntary compliance by organizations with their own policies and procedures, without any external oversight or enforcement from government agencies or regulators1, p. 63-64 References: 1: CDPSE Review Manual (Digital Version)

Data flows are the most important to review before using an application programming interface (API) to help mitigate related privacy risk. Data flows are the paths or routes that data take from their sources to their destinations through various processes, transformations, or exchanges. Data flows can help understand how data are collected, used, shared, stored, or deleted by an API and its related applications. Data flows can also help identify the potential privacy risks or impacts that may arise from data processing activities involving an API and its related applications. Data flows can be represented by diagrams, maps, models, or documents that show the sources, destinations, types, formats, volumes, frequencies, purposes, or legal bases of data.

Data taxonomy, data classification, and data collection are also important for privacy risk mitigation when using an API, but they are not the most important. Data taxonomy is a system of organizing and categorizing data into groups, classes, or hierarchies based on their characteristics, attributes, or relationships. Data taxonomy can help understand the structure, meaning, context, or value of data. Data classification is a process of assigning labels or tags to data based on their sensitivity, confidentiality, criticality, or risk level. Data classification can help determine the appropriate level of protection or handling for data. Data collection is a process of gathering or obtaining data from various sources for a specific purpose or objective. Data collection can help obtain the necessary information or evidence for decision making or problem solving.

References: Critical API security risks: 10 best practices | TechBeacon, Open APIs and Security Risks | Govenda Board Portal Software, The top API security risks and how to mitigate them - Appinventiv

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

The best way to ensure data confidentiality across databases is to use data anonymization, which is a process of removing or modifying personal or sensitive data from a dataset so that it cannot be linked or attributed to a specific individual or entity. Data anonymization helps protect the privacy and security of the data subjects, as well as comply with the applicable data protection laws and regulations. Data anonymization can be achieved by using various techniques, such as masking, encryption, aggregation, generalization, perturbation, or synthetic data generation12.

References:

• CDPSE Review Manual, Chapter 3 – Data Lifecycle, Section 3.3 – Data Anonymization3.
• CDPSE Certified Data Privacy Solutions Engineer All-in-One Exam Guide, Chapter 3 – Data Lifecycle, Section 3.4 – Data Anonymization4.

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.

References:

• 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

The best way for an organization to maintain the effectiveness of its privacy breach incident response plan is to conduct annual data privacy tabletop exercises. A tabletop exercise is a simulated scenario that tests the organization’s ability to respond to a privacy breach incident in a realistic and interactive way. A tabletop exercise can help the organization to evaluate the roles and responsibilities of the incident response team, identify the gaps and weaknesses in the plan, improve the communication and coordination among the stakeholders, and update the plan based on the lessons learned and best practices12. A tabletop exercise can also enhance the awareness and readiness of the organization to handle privacy breach incidents in a timely and effective manner3. References:

• ISACA CDPSE Review Manual, Chapter 4, Section 4.3.2
• ISACA Journal, Volume 4, 2019, “Tabletop Exercises: Three Sample Scenarios”
• ISACA Journal, Volume 6, 2017, “Privacy Breach Response: Preparing for the Inevitable”

The right to be forgotten is a privacy right that allows individuals to request the deletion or removal of their personal data from a data controller’s records or systems under certain conditions. One of these conditions is when the data is no longer required for the purpose originally collected, meaning that the data has become obsolete, irrelevant or excessive for fulfilling the initial purpose for which it was obtained or processed by the data controller. The other options are not valid conditions for exercising the right to be forgotten. The data is being used to comply with legal obligations or public interest is an exception that may prevent the data controller from deleting or removing the data upon request, as there may be overriding legitimate grounds for retaining the data for legal compliance or public interest reasons. The individual objects despite legitimate grounds for processing is a condition for exercising the right to object, not the right to be forgotten, which allows individuals to oppose the processing of their personal data based on their particular situation or for direct marketing purposes. The individual’s legal residence status has recently changed is not a relevant factor for exercising the right to be forgotten, as it does not affect the necessity or relevance of the data for its original purpose1, p. 107-108 References: 1: CDPSE Review Manual (Digital Version)

The first step for an IT privacy practitioner following a decision to expand remote working capability is to evaluate the impact resulting from this change on the organization’s privacy policies, programs and practices. This will help identify the risks and gaps that need to be addressed, as well as the opportunities for improvement and optimization. The other options are possible actions that may be taken after the impact assessment, depending on the results and recommendations.

References:

• CDPSE Exam Content Outline, Domain 1 – Privacy Governance (Governance, Management & Risk Management), Task 1: Identify issues requiring remediation and opportunities for process improvement1.
• CDPSE Review Manual, Chapter 1 – Privacy Governance, Section 1.3 – Privacy Impact Assessment (PIA)2.

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)

Remote employee monitoring software is a solution that collects, analyzes and reports data on the activities and behaviors of employees who work remotely or from home. It can help organizations to measure and improve employee productivity, performance, engagement and security. However, it also poses significant privacy risks and challenges, as it may involve the collection and processing of personal data, such as names, email addresses, biometric data, IP addresses, keystrokes, screenshots, web browsing history, app usage, communication content and frequency, etc.

Data access should be restricted based on roles, meaning that only authorized and legitimate parties should be able to access and use the data collected by the remote employee monitoring software, based on their roles and responsibilities within the organization. This is a key privacy principle and practice that helps to protect the privacy rights and interests of the employees, and to prevent unauthorized or excessive access, use, disclosure or modification of their personal data by the organization or third parties. Data access restriction based on roles 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.

References:

• Mobile Workforce Security Considerations and Privacy - ISACA, section 3: “The principle of least privilege should be applied to ensure that only authorized personnel have access to the data.”
• Why Employee Privacy Matters More Than Ever - ISACA, section 3: “Privacy-first monitoring should include granular privacy controls, including: Auto-redacting personal information; Restricting access to sensitive information based on role; Masking sensitive information from view.”

The most important information to capture in the audit log of an application hosting personal data is the last user who accessed personal data. This is because the audit log is a record of the activities and events that occur within the application, such as user actions, system events, errors, or exceptions. The audit log helps to monitor and verify the compliance, security, and performance of the application, as well as to detect and investigate any incidents or anomalies. Capturing the last user who accessed personal data in the audit log helps to ensure the accountability and traceability of the data access, as well as to identify and prevent any unauthorized or inappropriate use, disclosure, or modification of personal data.

References: CDPSE Review Manual, 2021, p. 147

When contracting with a SaaS provider, it is important to ensure that the provider will remove all customer data from their systems and storage devices at the end of the service contract. This will prevent any unauthorized access, use, or disclosure of the customer data by the provider or third parties after the service termination. Removal of customer data means that the data are permanently erased and cannot be recovered or restored by any means.

References:

• ISACA, Data Privacy Audit/Assurance Program, Control Objective 9: Data Disposal, p. 16-171
• ISACA, CDPSE Review Manual 2021, Chapter 4: Privacy Incident Response, Section 4.2: Data Disposal and Destruction, p. 151-152.

A privacy notice is a document that informs data subjects about how their personal data is collected, processed, stored, shared, and protected by an organization. The primary purpose of a privacy notice is to provide transparency to the data subject on the intended use of their personal data, as well as their rights and choices regarding their data. A privacy notice also helps the organization comply with legal and regulatory requirements, such as obtaining consent, demonstrating accountability, and fulfilling the principle of fairness and lawfulness.

References: CDPSE Review Manual, 2021, p. 36

Before de-identifying data, it is important to determine the categories of personal data collected, such as names, addresses, phone numbers, email addresses, social security numbers, health information, and so on. This will help to identify which data elements are considered identifiers or quasi-identifiers, and which de-identification techniques are appropriate for each category. For example, some data elements may need to be removed completely, while others may be masked, generalized, or perturbed.

References:

• Anonymize and De-identify | Research Data Management
• Data De-identification: An Overview of Basic Terms - ed

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;