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IAPP-CIPT exam Format | IAPP-CIPT Course Contents | IAPP-CIPT Course Outline | IAPP-CIPT exam Syllabus | IAPP-CIPT exam Objectives

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.

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