IAPP CIPT - Certified Information Privacy Technologist

A valid argument against data minimization is that it Can limit business opportunities. Data minimization is the principle that data collected should be limited to what is necessary for the purposes for which it is processed. While this principle supports privacy and data protection, it can also restrict the amount of data available to businesses for analysis and innovation, potentially limiting their ability to develop new products, improve services, or identify new market opportunities.

Public key infrastructure (PKI) relies heavily on the trustworthiness of certificate authorities (CAs). These CAs are responsible for issuing and verifying digital certificates. If a CA is compromised or disreputable, the entire PKI system's integrity can be undermined because the certificates it issues can no longer be trusted. This can lead to a range of security issues, including the potential for man-in-the-middle attacks, as malicious actors could exploit compromised certificates to impersonate legitimate entities. Thus, maintaining reputable and secure CAs is critical to the PKI system's effectiveness.

FAIR (Factor Analysis of Information Risk) analysis is a structured approach to understanding, analyzing, and quantifying information risks. The core factors in FAIR analysis include the severity of the harm (option A), the capability of a threat actor (option B), and the probability of a threat actor's success (option D). The stage of the data life cycle, while important in understanding data management practices, is not a direct factor in the FAIR analysis framework. According to IAPP documentation, FAIR analysis focuses on quantifying risk factors to evaluate and manage privacy risks effectively, emphasizing measurable and actionable components rather than the data life cycle stage.

The OECD Privacy Principles became a foundation for privacy principles and practices of countries and organizations across the globe. Established in 1980, these principles provided a comprehensive framework that has influenced many national and international privacy laws. The OECD Privacy Principles focus on critical aspects of data protection, such as collection limitation, data quality, purpose specification, use limitation, security safeguards, openness, individual participation, and accountability, forming a basis for global privacy standards (IAPP, Certified Information Privacy Technologist (CIPT) materials).

Record encryption provides a more granular level of security compared to disk, file, or table encryption. It encrypts individual records within a database, which means that even if a breach occurs, the exposure is limited to the specific records accessed rather than the entire database or table. This granular approach minimizes the potential damage and data loss in case of a security breach. Additionally, it allows for more precise control over access and decryption, enhancing overall security measures within the facility.

Drone "swarming" refers to multiple drones communicating and coordinating with each other to accomplish a task. This involves a group of drones that work together in a cohesive and synchronized manner. In the example given, drones performing a search and rescue by communicating and working together fits the definition of swarming. This collaborative approach leverages the capabilities of multiple drones to cover more ground efficiently and effectively, as supported by IAPP documents on the application of drone technology in coordinated activities.

Option A: Encrypted computation focuses on protecting the privacy of data while allowing computations to be performed on it. It does not address the relevance of ads to users, which is a separate issue related to the effectiveness of the ad targeting algorithm.

Option B: Encrypted computation aims to protect the user's sensitive personal information by ensuring it remains encrypted during the computation process, thus mitigating this privacy risk.

Option C: Encrypted computation prevents the server from discerning personal information as the data remains encrypted throughout the process.

Option D: By maintaining encryption, encrypted computation also helps prevent information leaks due to weak de-identification techniques.

References:

IAPP CIPT Study Guide

Research papers on encrypted computation and privacy-preserving ad targeting

These detailed explanations provide context and references to ensure the answers align with the IAPP Information Privacy Technologist documents and best practices.

Differential identifiability is a method used to ensure that data cannot be re-identified to individual users, which is crucial when dealing with sensitive information like health conditions. This method can help strengthen privacy controls by applying mathematical techniques to anonymize data while preserving its utility for analysis.

To meet data protection and privacy legal requirements regarding the disposal or deletion of personal data when it is no longer necessary, the best privacy-enhancing solution involves integrating robust application logic. Option C suggests developing application logic that validates and purges personal data according to its legal hold status or retention schedule. This approach ensures compliance with legal mandates for data retention and deletion, minimizing the risk of retaining unnecessary personal data. References to this can be found in IAPP’s CIPT materials, specifically in the sections discussing data lifecycle management and legal compliance requirements.

An acceptable disclosure practice involves transparently informing individuals about how their data will be used within the organization. This includes specifying data usage among different groups or departments within the organization. It is essential for maintaining trust and compliance with privacy regulations. The IAPP highlights that clear and comprehensive privacy policies help ensure that individuals are aware of the internal data flows and purposes, thus meeting legal and ethical standards (IAPP, "Privacy Policies and Notices").