Use this quick start guide to collect all the information about IAPP CIPT Certification exam. This study guide provides a list of objectives and resources that will help you prepare for items on the IAPP Certified Information Privacy Technologist (CIPT) exam. The Sample Questions will help you identify the type and difficulty level of the questions and the Practice Exams will make you familiar with the format and environment of an exam. You should refer this guide carefully before attempting your actual IAPP Certified Information Privacy Technologist (CIPT) certification exam.
The IAPP CIPT certification is mainly targeted to those candidates who want to build their career in Privacy Laws and Regulations domain. The IAPP Certified Information Privacy Technologist (CIPT) exam verifies that the candidate possesses the fundamental knowledge and proven skills in the area of IAPP Information Privacy Technologist.
IAPP CIPT Exam Summary:
| Exam Name | IAPP Certified Information Privacy Technologist (CIPT) |
| Exam Code | CIPT |
| Exam Price |
USD $First Time Candidate: $550 Retake: $375 |
| Duration | 150 mins |
| Number of Questions | 90 |
| Passing Score | 300 / 500 |
| Books / Training | Privacy in Technology (CIPT) |
| Schedule Exam | Pearson VUE |
| Sample Questions | IAPP CIPT Sample Questions |
| Practice Exam | IAPP CIPT Certification Practice Exam |
IAPP Information Privacy Technologist Exam Syllabus Topics:
| Topic | Details |
|---|---|
Foundational principles |
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| Demonstrate knowledge of privacy risk models and frameworks and their roles in laws and guidance. |
- Apply FIPPs and OECD principles. - Apply privacy frameworks (e.g., NIST/NICE, ISO/IEC 27701 and BS10012 Privacy Information Management System). - Apply the concept of Nissenbaum’s Contextual Integrity. - Apply Calo’s Harms Dimensions. - Apply the Factor Analysis in Information Risk (FAIR) model. |
| Demonstrate knowledge of privacy by design principles. |
- Apply the principle of end-to-end security — full life cycle protection. - Apply the principle of privacy embedded into design. - Apply the principle of full functionality — positive-sum not zero-sum. - Apply the principle of visibility and transparency. - Apply the principle of proactive not reactive. - Apply the principle of privacy by default. - Apply the principle of respect for user privacy. |
| Demonstrate knowledge of Privacy-related Technology Fundamentals. |
- Understand risk concepts (e.g., threat, vulnerability, attack, security exploit). - Recognize the occurrence of a personal data breach and other types of privacy incidents. - Identify privacy and security practices within an organization. - Recognize how technology supports information governance in an organization. - Implement internal and external data protection and privacy notices. - Implement internal data protection and privacy policies, guidelines and procedures. - Analyze third-party contracts and agreements. - Catalog data assets, develop a data inventory and implement a Record of Processing Activities (RoPA). - Understand enterprise architecture and use of data flow diagrams/data lineage tools, including cross-border transfer considerations. - Complete data protection and privacy impact assessments (DPIA/PIAs). - Identify privacy-related key risk indicators (KRIs) and key performance indicators (KPIs). |
| Demonstrate knowledge of the data life cycle. |
- Recognize privacy’s role in data collection. - Recognize privacy’s role in data use. - Recognize privacy’s role in data disclosure. - Recognize privacy’s role in data transfer. - Recognize privacy’s role in data retention. - Recognize privacy’s role in data destruction. |
The privacy technologist’s role in the context of the organization |
|
| Identify and implement general 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). - Implement privacy standards and frameworks. - Analyze contractual and regulatory privacy and data protection requirements. - Translate legal and regulatory requirements into practical technical and/or operational solutions. - Consult on privacy notices and policies. |
| Identify and implement technical roles and responsibilities. |
- Analyze and implement technical measures for privacy and security practices. - Advise on the privacy implications of new uses of existing technologies or new and emerging technologies. - Advise on the effective selection and implementation during development or acquisition of products that impact privacy. - Advise on privacy and data protection impact assessments (PIAs and DPIAs) in system development. - Advise on privacy by design implementation via privacy engineering in systems engineering processes. - Support individual’s’ privacy rights requests (e.g., access, deletion). - Support records of processing activities (RoPAs), data inventories and data flow mapping. - Support oversight of technical elements of privacy operations and audits, including third-party assessments. - Develop, compile, report, and monitor privacy key risk indicators (KRIs) and key performance indicators (KPIs). - Provide technical privacy support to identify and respond to privacy breaches and other types of incidents. |
Privacy risks, threats and violations |
|
| 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 access to 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. |
- Minimize privacy risk involved when collecting personal data from individuals. - Employ privacy-enhancing techniques for high-risk personal data processing methods (e.g., tracking, surveillance). - Demonstrate understanding of consent requirements when collecting personal data. - Implement measures to manage privacy risks associated with automatic collection of personal data. - Implement measures to correct personal data inaccuracies. - Leverage techniques to minimize risk when extracting personal data from publicly available sources. - Understand the jurisdictional implications of personal data collection (e.g., localization, government access). |
| Demonstrate how to minimize privacy risk during personal data use. |
- Use technical approaches that minimize the risks associated with:
|
| Demonstrate how to minimize privacy risk during personal data dissemination. |
- Use technical approaches that minimize the risks associated with disclosure and accessibility. - Leverage approaches and techniques that minimize the threat of:
|
| Demonstrate how to minimize the threat of intrusion and decisional interference. |
- Implement technical approaches that minimize the risks associated with the use of behavioral advertising. - Employ technical approaches that minimize the threat of cyberbullying. - Use technical approaches that minimize the threat of social engineering. - Avoid the use of dark patterns that limit privacy-preserving response options. |
| Identify privacy risks related to software security. |
- Understand measures to fix software vulnerabilities. - Leverage intrusion detection and prevention tools and techniques. - Implement measures to reduce privacy risks during change management (e.g., patches, upgrades). - Utilize open-source versus closed-source software. - Recognize possible privacy violations by service providers. |
Privacy-enhancing strategies, techniques and technologies |
|
| Identify and implement appropriate data oriented strategies. |
- Implement data processing segregation to mitigate risk of linking and correlating personal data with other datasets. - De-identify personal data by making it un-linkable or unobservable so that it cannot be discovered or traced back to its original user/identifier. - Minimize personal data collection and use only what is necessary for the purposes for which the data was originally collected. - Abstract personal data by reducing data precision while maintaining data accuracy and suitability for a specific use case. |
| Identify and implement appropriate process-oriented strategies. |
- Inform individuals about how their personal data is processed. - Provide data subjects with control over the processing of their personal data, including the ability to consent to data collection, use, disclosure, retention and destruction. - Enforce processing of personal data that aligns with privacy risk reduction in policies and procedures. - Demonstrate compliance with privacy laws, regulations, standards, frameworks, guidelines, policies and procedures. |
| Identify and implement appropriate data protection strategies (e.g., privacy-enhancing techniques). |
- Use data analysis and other procedures and techniques to minimize the privacy risk associated with the aggregation of personal data. - Employ privacy-enhancing techniques (e.g., anonymization or pseudonymization) to reduce risk exposure. - Implement de-identification techniques (e.g., encryption) to protect personal data. - Implement other defense in-depth techniques (e.g., identity and access management, authentication mechanisms) to protect personal data from risk exposure. - Understand and effectively navigate the technological implications of requirements stemming from privacy regulations and the relevant techniques needed to address them:
|
Privacy by design |
|
| Implement the privacy by design methodology. |
- Define and communicate privacy goals and objectives to guide privacy by design within an organization. - Document privacy requirements encompassing regulatory and organizational policies to ensure alignment with privacy by design principles. - Incorporate privacy considerations into the design process by understanding relevant quality attributes, such as predictability, manageability and disassociability. - Demonstrate how the principles of privacy risk are embedded into the design process. - Interpret high-level specifications and align them via low-level specifications with the privacy by design principles. |
| Evaluate privacy risks in user experiences. |
- Assess potential impact of design choices on user behavior. - Incorporate understanding of user experience (UX) concepts into the design of privacy-related functions. - Implement clear and accessible privacy notices, settings and consent management mechanisms. - Perform usability testing where relevant to assess effectiveness of privacy-related functions. |
| Implement Value Sensitive Design. |
- Understand how value sensitive design affects users. - Apply value sensitive design aligned with privacy by design principles. |
| Manage and monitor privacy- related functions and controls. |
- Conduct privacy audits and IT control reviews. - Conduct code reviews to identify potential privacy gaps that require attention. - Conduct runtime behavior monitoring. - Implement data management practices in production and nonproduction environments. |
Privacy engineering |
|
| Understand the role of privacy engineering in the organization. |
- Recognize aspects of effective implementation of privacy engineering. - Identify technological controls to use for privacy engineering. - Integrate privacy into the system development life cycle. |
| Understand and implement privacy engineering objectives. |
- Apply predictability in privacy engineering activities. - Apply manageability in privacy engineering activities. - Apply disassociability in privacy engineering activities. |
| Identify and evaluate privacy design patterns. |
- Recognize which privacy preserving design patterns to emulate. - Recognize which dark patterns to avoid. |
| Manage privacy risks in the development life cycle. |
- Impose multifaceted privacy controls throughout the development life cycle:
|
Evolving or Emerging Technologies in Privacy |
|
| Understand the privacy implications of the use of robotics and Internet of Things (IoT). |
- Identify and minimize privacy risk involved when using wearable devices. - Identify and minimize privacy risk involved when using smart home devices and IoT technology for smart cities (e.g., CCTV, tracking/surveillance). - Identify and minimize privacy risk involved when using robots, including drones. |
| Understand the privacy implications of the use of e-commerce. |
- Identify and minimize privacy risk involved when using adtech. - Identify and minimize privacy risk involved when using cookies and other web tracking technologies. - Identify and minimize privacy risk involved when using alerts and notifications. - Identify and minimize privacy risk involved when using location tracking. - Identify and minimize privacy risk involved when using chatbots. - Identify and minimize privacy risk involved when using behavioral profiling. - Identify and minimize privacy risk involved when using online/mobile payments. |
| Understand the privacy implications of the use of biometrics. |
- Identify and minimize privacy risk involved when using facial recognition. - Identify and minimize privacy risk involved when using speech recognition. - Identify and minimize privacy risk involved when using fingerprint identification. - Identify and minimize privacy risk involved when using DNA. |
| Understand the privacy implications of the use of technology in the workplace. |
- Identify and minimize privacy risk involved when using shared data centers. - Identify and minimize privacy risk involved when using data management and analytics. - Identify and minimize privacy risk involved when using third-party vendor IT solutions. - Identify and minimize privacy risk involved when using remote work. - Identify and minimize privacy risk involved when using video calls and conferencing. - Identify and minimize privacy risk involved when using Next Gen infrastructure deployment models (e.g., edge computing, cloud-based infrastructure). - Identify and minimize privacy risk involved when using artificial intelligence (AI), machine learning (ML) and deep learning. - Identify and minimize privacy risk involved when using quantum computing. - Identify and minimize privacy risk involved when using blockchain, cryptocurrencies and non-fungible tokens (NFT). - Identify and minimize privacy risk involved when using virtual/augmented reality. |
| Understand the privacy implications of the use of communications technologies. |
- Identify and minimize privacy risk involved when using online platforms providing communications via text, voice, video and/or photo (e.g., social media, gaming platforms). - Identify and minimize privacy risk involved when using mobile devices. - Identify and minimize privacy risk involved when using messaging and video calling. |
To ensure success in IAPP Information Privacy Technologist certification exam, we recommend authorized training course, practice test and hands-on experience to prepare for IAPP Certified Information Privacy Technologist (CIPT) exam.