Compartmentalizing resource access is a security technique that divides a system or network into separate segments or zones with different levels of access and control, based on the sensitivity and value of the data or resources. Compartmentalizing resource access would most effectively reduce the impact of a successful breach through a remote access solution, as it would limit the scope and extent of the breach, and prevent unauthorized access to other segments or zones that contain more critical or sensitive data or resources. The other options are not as effective as compartmentalizing resource access in reducing the impact of a successful breach through a remote access solution. Regular testing of system backups is a security technique that verifies the availability and recoverability of data in case of a system failure or disaster, but it does not prevent or limit unauthorized access to data. Monitoring and reviewing remote access logs is a security technique that records and analyzes the activities and events related to remote access sessions, but it does not prevent or limit unauthorized access to data.Regular physical and remote testing of the incident response plan is a security technique that evaluates and improves the readiness and effectiveness of an organization's response to security incidents, but it does not prevent or limit unauthorized access to data1, p.91-92Reference:1: CDPSE Review Manual (Digital Version)

Anonymization is a technique that removes or modifies all identifiers in a data set to prevent or limit the identification of the data subjects. Anonymization is an IT privacy practitioner's best recommendation to reduce privacy risk before an organization provides personal data to a third party, as it would protect the privacy of the data subjects by reducing the linkability of the data set with their original identity, and also comply with the data minimization principle that requires limiting the collection, storage and processing of personal data to what is necessary and relevant for the intended purposes. Anonymization would also preserve some characteristics or patterns of the original data that can be used for analysis or research purposes by the third party, without compromising the accuracy or quality of the results. The other options are not as effective as anonymization in reducing privacy risk before an organization provides personal data to a third party. Tokenization is a technique that replaces sensitive or confidential data with non-sensitive tokens or placeholders that do not reveal the original data, but it does not prevent or limit the identification of the data subjects, as tokens can be reversed or linked back to the original data using a tokenization system or key. Aggregation is a technique that combines individual data into groups or categories that do not reveal the identity of the data subjects, but it may not prevent or limit the identification of the data subjects, as aggregated data can be de-aggregated or re-identified using other sources of information or techniques.Encryption is a technique that transforms plain text data into cipher text using an algorithm and a key, making it unreadable by unauthorized parties, but it does not prevent or limit the identification of the data subjects, as encrypted data can be decrypted or linked back to the original data using an encryption system or key1, p.74-75Reference:1: CDPSE Review Manual (Digital Version)

User behavior analytics tools are the best control to detect potential internal breaches of personal data because they monitor and analyze the activities and patterns of users on the network and systems, and alert or block any anomalous or suspicious behavior that may indicate unauthorized access, misuse or exfiltration of personal data. Data loss prevention (DLP) systems, employee background checks and classification of data are useful controls to prevent or mitigate internal breaches of personal data, but they do not necessarily detect them.

CDPSE Review Manual (Digital Version), Domain 2: Privacy Architecture, Task 2.4: Design and/or implement privacy controls1

CDPSE Certified Data Privacy Solutions Engineer All-in-One Exam Guide, Chapter 3: Privacy Architecture, Section: Privacy Controls2

De-identification is a technique that removes or modifies direct and indirect identifiers in a data set to prevent or limit the identification of the data subjects. De-identification reduces the risk of re-identification and thus limits the organization's potential exposure in the event of consumer data loss. De-identification also maintains the traceability of the data by preserving some characteristics or patterns of the original data that can be used for analysis or research purposes.The other options are not effective ways to limit exposure and maintain traceability1, p.75-76Reference: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.