An organization is developing a wellness smartwatch application and is considering what information should be collected from the application users. Which of the following is the MOST legitimate information to collect for business reasons in this situation?
Correct Answer: A
Height, weight, and activities are the most legitimate information to collect for business reasons in this situation, as they are directly related to the purpose and functionality of a wellness smartwatch application that aims to monitor and improve the health and fitness of its users. Collecting height, weight, and activities would 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. The other options are not legitimate information to collect for business reasons in this situation, as they are not related to the purpose and functionality of a wellness smartwatch application and may violate the privacy rights and preferences of its users. Collecting sleep schedule and calorie intake may be useful for some users who want to track their sleep quality and nutrition intake, but they are not essential for a wellness smartwatch application and may require additional consent or justification from the users. Collecting education and profession may be irrelevant for a wellness smartwatch application and may be used for other purposes, such as marketing or profiling, without the consent or knowledge of the users. Collecting race, age, and gender may be sensitive for some users who do not want to disclose their personal characteristics or identity, and may require additional safeguards or measures to protect their privacy1, p. 75-76 Reference: 1: CDPSE Review Manual (Digital Version)
Question 92
Which of the following is the BEST method to ensure the security of encryption keys when transferring data containing personal information between cloud applications?
Correct Answer: B
Explanation 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.
Question 93
Which of the following should be done FIRST before an organization migrates data from an on-premise solution to a cloud-hosted solution that spans more than one jurisdiction?
Correct Answer: D
Explanation The best answer is D. Assess the organization's exposure related to the migration. A comprehensive explanation is: Before an organization migrates data from an on-premise solution to a cloud-hosted solution that spans more than one jurisdiction, it should first assess its exposure related to the migration. This means that the organization should identify and evaluate the potential risks and benefits of moving its data to the cloud, taking into account the legal, regulatory, contractual, and ethical obligations and implications of doing so. Some of the factors that the organization should consider in its assessment are: The nature, sensitivity, and value of the data being migrated, and the impact of its loss, theft, corruption, or disclosure on the organization and its stakeholders. The security, privacy, and compliance requirements and standards that apply to the data in each jurisdiction where it is stored, processed, or accessed, and the differences or conflicts among them. The trustworthiness, reliability, and reputation of the cloud service provider and its subcontractors, and the terms and conditions of their service level agreements (SLAs) and contracts. The availability, performance, scalability, and cost-effectiveness of the cloud-hosted solution compared to the on-premise solution, and the trade-offs involved. The technical feasibility and complexity of migrating the data from the on-premise solution to the cloud-hosted solution, and the tools and methods needed to do so. The organizational readiness and capability to manage the change and transition from the on-premise solution to the cloud-hosted solution, and the training and support needed for the staff and users. By conducting a thorough assessment of its exposure related to the migration, the organization can make an informed decision about whether to proceed with the migration or not, or under what conditions or modifications. The assessment can also help the organization to plan and implement appropriate measures and controls to mitigate or avoid any negative consequences and enhance or maximize any positive outcomes of the migration. Ensuring data loss prevention (DLP) alerts are turned on (A), encrypting the data while it is being migrated (B), and conducting a penetration test of the hosted solution are all good practices to protect data privacy and security when migrating data from an on-premise solution to a cloud-hosted solution that spans more than one jurisdiction. However they are not the first steps that should be done before the migration. They are more relevant during or after the migration process. They also do not address other aspects of exposure related to the migration, such as legal, regulatory, contractual, or ethical issues. References: Data Migration: On-Premise to Cloud - 10 Steps to Success1 8 Best Practices for On-Premises to Cloud Migration2 5 Steps for a Successful On-Premise to Cloud Migration3 Extend on-premises data solutions to the cloud4 On Premise to Cloud migration tool5
Question 94
Which of the following is the BEST course of action to prevent false positives from data loss prevention (DLP) tools?
Correct Answer: D
Explanation The best course of action to prevent false positives from data loss prevention (DLP) tools is to re-establish baselines for configuration rules. False positives are events that are triggered by a DLP policy in error, meaning that the policy has mistakenly identified non-sensitive data as sensitive or blocked legitimate actions. False positives can reduce the effectiveness and efficiency of DLP tools by generating unnecessary alerts, wasting resources, disrupting workflows, and creating user frustration. To avoid false positives, DLP tools need to have accurate and updated configuration rules that define what constitutes sensitive data and what actions are allowed or prohibited. Configuration rules should be based on clear and consistent criteria, such as data classification levels, data sources, data destinations, data formats, data patterns, user roles, user behaviors, etc. Configuration rules should also be regularly reviewed and adjusted to reflect changes in business needs, regulatory requirements, or threat landscape. Conducting additional discovery scans, suppressing the alerts generating the false positives, or evaluating new DLP tools are not the best ways to prevent false positives from DLP tools. Conducting additional discovery scans may help identify more sensitive data in the network, but it does not address the root cause of false positives, which is the misconfiguration of DLP policies. Suppressing the alerts generating the false positives may reduce the noise and annoyance caused by false positives, but it does not solve the problem of inaccurate or outdated DLP policies. Evaluating new DLP tools may offer some advantages in terms of features or performance, but it does not guarantee that false positives will be eliminated or reduced without proper configuration and tuning of DLP policies. References: False Positives Handling| Endpoint Data Loss Prevention - ManageEngine ..., Scenario-based troubleshooting guide - DLP Issues, Respond to a DLP policy violation in Power BI - Power BI
Question 95
Which of the following information would MOST likely be considered sensitive personal data?
Correct Answer: C
Explanation Sensitive personal data is a subset of personal data that reveals or relates to more intimate or confidential aspects of a person's identity, such as their racial or ethnic origin, religious or philosophical beliefs, health status, sexual orientation, political opinions, trade union membership, biometric or genetic data, or criminal record. Sensitive personal data is subject to more stringent legal and regulatory protections and requires a higher level of consent from the data subject to be processed. Mailing address, bank account login ID, and contact phone number are examples of personal data, but not sensitive personal data, as they do not reveal or relate to such intimate or confidential aspects of a person's identity. References: CDPSE Review Manual, 2021, p. 29
