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A global financial institution is implementing data masking technology to protect personal data used for testing purposes in non-production environments. Which of the following is the GREATEST challenge in this situation?
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.
Which type of data is produced by using a more complex method of analytics to find correlations between data sets and using them to categorize or profile people?
Which cloud deployment model is BEST for an organization whose main objectives are to logically isolate personal data from other tenants and adopt custom privacy controls for the data?
A private cloud is a cloud deployment model that provides exclusive access and control to a single organization or a specific group of users within the organization. A private cloud is best for an organization whose main objectives are to logically isolate personal data from other tenants and adopt custom privacy controls for the data, as it offers the highest level of security, privacy, and customization among the cloud deployment models. A private cloud allows the organization to implement its own privacy policies, standards, and procedures for the personal data, as well as to configure the cloud infrastructure, services, and applications according to its specific needs and preferences. A private cloud also reduces the risk of data breaches, unauthorized access, or co-mingling of data from other tenants, as the personal data is stored and processed in a dedicated and isolated environment.
An organization wants to ensure that endpoints are protected in line with the privacy policy. Which of the following should be the FIRST consideration?
The first consideration for ensuring that endpoints are protected in line with the privacy policy is hardening the operating systems of endpoint devices. Hardening is a process of applying security configurations and controls to reduce the attack surface and vulnerabilities of an operating system. Hardening can include disabling unnecessary services and features, applying security patches and updates, enforcing strong passwords and encryption, configuring firewall and antivirus settings, and implementing least privilege principles. Hardening the operating systems of endpoint devices can help prevent unauthorized access, data leakage, malware infection, or other threats that may compromise the privacy of personal data stored or processed on those devices.
Detecting malicious access through endpoints, implementing network traffic filtering on endpoint devices, and managing remote access and control are also important aspects of endpoint security, but they are not the first consideration. Rather, they are dependent on or complementary to hardening the operating systems of endpoint devices. For example, detecting malicious access requires having a baseline of normal activity and behavior on the endpoint device, which can be established by hardening. Implementing network traffic filtering requires having a firewall or other network security tool installed and configured on the endpoint device, which is part of hardening. Managing remote access and control requires having authentication and authorization mechanisms in place on the endpoint device, which is also part of hardening.
Which of the following is the BEST way to protect the privacy of data stored on a laptop in case of loss or theft?
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.
