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Exam Code: IAPP-CIPT
Exam Name: Certified Information Privacy Technologist
Total Questions: 90 multiple-choice questions (75 scored questions and 15 unscored questions)
Time Allotted: 2.5 hours (150 minutes) with a 15-minute break
Passing Score: 300 out of 500 scaled points

- Identify and implement legal and procedural roles and responsibilities.
- Understand various roles and responsibilities related to the privacy function (e.g.- Data Governance [DPO- Data Owner- Data Steward- Data Custodian]- legal compliance- cybersecurity).
- Translate legal and regulatory requirements into practical technical and/or operational solutions.
- Implement internal and external data protection and privacy notices- policies- guidelines and procedures.

- Identify and implement technical roles and responsibilities.
- Oversee technical elements of privacy operations and audits including third-party exams.
- Provide technical privacy support to identify and respond to privacy breaches and other types of incidents.
- Understand risk concepts (e.g.- threat- vulnerability- attack- security exploit).

- Demonstrate knowledge of privacy risk models and frameworks and their roles in legal requirements and guidance.
- Apply common privacy risk models and frameworks (e.g.- Nissenbaums Contextual Integrity- Calos Harms Dimensions- Factor Analysis in Information Risk (FAIR) model- NIST/NICE framework- FIPPS- OECD principles).
- Understand and apply common privacy threat models and frameworks (e.g.- LINDDUN and MITRE PANOPTIC™).

- Understand the connection between data ethics and data privacy.

- Differentiate legal versus ethical processing of personal data (e.g.- when comparing different jurisdictions).
- Understand the social and ethical issues when advising on privacy impacting designs and technologies (e.g.- unlawful or unauthorized accessto personal data- manipulating societal conversations and attitudes on controversial topics).
- Identify and minimize bias/discrimination when advising/designing tools with automated decision-making (e.g.- incorporating personal preference into data decisions).

- Demonstrate how to minimize privacy risk during personal data collection.

- Understand and apply requirements to provide data subjects with control over the processing of their personal data including consent requirements for personal data collection- use- disclosure- and retention (e.g.- clear and accessible privacy notices- settings- dashboards- other consent management mechanisms).
- Implement measures to manage privacy risks associated with automatic collection of personal data.
- Leverage techniques to minimize risk when extracting personal data from publicly available sources.
- Practice appropriate data retention and destruction techniques.

- Demonstrate how to minimize privacy risk during personal data use.

- Practice appropriate data minimization techniques (e.g.- abstract personal data for a specific use case).
- Implement data processing segregation.
- Use data analysis and other procedures to minimize privacy risk associated with the aggregation of personal data.
- Employ appropriate privacy-enhancing techniques (e.g.- anonymization- pseudonymization- differential privacy) to reduce risk exposure.
- Use technical approaches that minimize the risks associated with secondary uses of personal data (e.g.- profiling).

- Demonstrate how to minimize privacy risk during personal data dissemination.

- Use technical approaches that minimize risks associated with disclosure and accessibility.
- Leverage approaches and techniques that minimize the threat of:
- a. Data distortion.
- b. Data exposure.
- c. Breach of confidentiality (personal data breaches).
- d. Blackmail.
- e. Appropriation.
- Implement other defense in-depth techniques (e.g.- identity and access management- authentication mechanisms) to protect personal data from risk exposure.

- Demonstrate how to minimize the threat of intrusion and decisional interference.

- Implement technical approaches that minimize the risks of various types of interference (e.g.- behavioral advertising- behavioral profiling- cyberbullying- social engineering).
- Avoid the use of dark patterns that limit privacy-preserving response options- and recognize which design patterns to emulate.

- Identify privacy risks related to software security.

- Implement measures to detect and fix software privacy vulnerabilities.
- Leverage intrusion detection and prevention tools and techniques.
- Implement measures to reduce privacy risks during change management (e.g.- patches- upgrades).
- Recognize possible privacy violations by service providers.

- Understand the privacy risks and impact of techniques that enable tracking and surveillance.

- Understand the privacy risks and impact associated with e-commerce (e.g.- behavioral advertising- cookies- chatbots- payments- behavioral profiling).
- Demonstrate knowledge of the privacy risks and impact of audio and video surveillance- including those involved in wearables and IoT technologies (e.g.- smart home devices and IoT technology for smart cities).
- Understand privacy issues around biometrics (e.g.- facial recognition- speech recognition- fingerprint identification- DNA).
- Demonstrate knowledge of the privacy risks and impacts of location tracking.
- Demonstrate knowledge of the privacy risks and impacts of internet monitoring

- Understand the privacy risks and impact involved when using workplace technologies.

- Identify and minimize privacy risks involved when using artificial intelligence- machine learning and deep learning.
- Identify and minimize privacy risk involved in the use of communications technologies (e.g.- video calls and conferencing- messaging- mobile devices- social media- gaming platforms).

- Demonstrate how to monitor and manage privacy risk

- Conduct privacy audits and IT control reviews.
- Develop- compile- report- and monitor privacy Key Risk In dicators and Key Performance Indicators.
- Complete privacy and data protection impact exams.

- Implement privacy by design principles.

- Understand and apply the seven privacy by design principles.
- Define and communicate privacy goals and objectives to guide privacy by design within an organization.
- Interpret high-level specifications and align them via low-level specifications with the privacy by design principles.

- Evaluate privacy risks in user experiences.

- Understand and apply UX concepts- including how UX decisions impact user behavior.
- Perform usability testing where relevant to assess effectiveness of privacy-related functions.
- Understand and apply value sensitive design.

- Understand and implement privacy engineering objectives.

- Apply the NIST Privacy Engineering Objectives: predictability- manageability and dissociability.
- Understand enterprise architecture- use of data flow diagrams/data lineage tools- including cross-border transfer considerations.
- Manage privacy risks in the development life cycle.

- Manage and monitor privacy-related functions and controls.

- Catalog data assets- develop a data inventory and implement a record of processing activities.
- Conduct code reviews to identify potential privacy gaps that require attention.
- Conduct runtime behavior monitoring.