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Data Privacy Question Bank

syllabus 

Question Bank 

DATA PRIVACY MTCSPE1001D 

UNIT I Questions

  1. Define data linking and profiling in the context of privacy. Discuss how these techniques can compromise individual privacy with relevant examples.
  2. Compare and contrast different access control models with special emphasis on role-based access control. How do they contribute to ensuring data privacy?
  3. Explain the concept of privacy policies. What are the key components that should be included in a well-designed privacy policy language?
  4. Discuss the unique privacy challenges in the medical domain. How do these challenges differ from those in the financial sector?
  5. Analyze how fundamental privacy concepts have evolved with the advancement of technology. Provide examples of how traditional definitions of privacy may be inadequate in today's digital environment.
  6. Evaluate the effectiveness of role-based access control in protecting sensitive information. What improvements can be made to strengthen its implementation?
  7. Discuss the ethical considerations that should be incorporated into privacy policies. How do these ethical frameworks influence policy development?
  8. Critically analyze the relationship between data privacy attacks and defensive measures. How has this relationship evolved over time?
  9. Compare different privacy policy specification languages. What are their relative strengths and limitations in practical implementations?
  10. Explain how the concept of privacy differs across cultures and legal systems. How should international organizations address these differences in their privacy frameworks?

UNIT II Questions

  1. Explain the concept of "data explosion" and analyze its implications for individual privacy in the digital age. Provide relevant statistics to support your answer.
  2. What are the primary barriers (or lack thereof) in the collection and distribution of person-specific information? Discuss both technical and non-technical factors.
  3. Describe a mathematical model for characterizing real-world data sharing practices. How can such models be used to compute privacy risks?
  4. Explain the relationship between demographics and uniqueness in the context of data privacy. How does this relationship impact re-identification risks?
  5. Compare different approaches to measuring privacy risks in datasets. What metrics are commonly used and what are their limitations?
  6. Analyze how advances in big data technologies have accelerated the data explosion phenomenon. What specific privacy challenges emerge from these technological developments?
  7. Discuss how the concept of "informed consent" has been affected by modern data collection practices. Is traditional consent still meaningful in today's data ecosystem?
  8. Evaluate the effectiveness of current mathematical models in quantifying privacy risks. What improvements could be made to make these models more accurate?
  9. Describe how uniqueness patterns in data can be exploited for re-identification. What demographic factors contribute most significantly to uniqueness?
  10. Compare the data sharing practices across different industries. How do their approaches to privacy protection differ and what factors influence these differences?

UNIT III Questions

  1. Compare and contrast the null-map, k-map, and wrong map protection models. What are the strengths and weaknesses of each approach?
  2. Explain the working principles of the Datafly system. How does it achieve privacy protection for delimited data?
  3. Analyze the k-Similar approach to privacy protection. In what scenarios is it most effective, and what are its limitations?
  4. Describe the methods used for inferring entity identities from supposedly anonymized data. How can organizations defend against such inference attacks?
  5. Explain how the Scrub system works to protect textual documents. What types of identifiers can it detect and sanitize?
  6. Evaluate the trade-off between data utility and privacy in different protection models. How can this balance be optimized for different use cases?
  7. Compare MinGen and Datafly systems in terms of their approaches, effectiveness, and computational efficiency. In what scenarios would you prefer one over the other?
  8. Analyze the technical challenges in implementing disclosure control mechanisms in large-scale databases. How can these challenges be addressed?
  9. Discuss the evolution of protection models from simple suppression techniques to more sophisticated approaches. What factors have driven this evolution?
  10.  Evaluate the effectiveness of current techniques for protecting textual data compared to structured data. What unique challenges does textual data present for privacy protection?

UNIT IV Questions

  1. Analyze the relationship between technology, policy, and freedom in the context of data privacy. How do these elements interact in shaping privacy outcomes?
  2. Discuss the key provisions of major medical privacy legislation. What protections do they offer to patients regarding their health information?
  3. Evaluate the effectiveness of current medical privacy best practices. What gaps exist and how might they be addressed?
  4. Compare privacy policies and practices in healthcare organizations before and after the implementation of medical privacy legislation. What changes have occurred?
  5. Discuss the challenges in balancing medical research needs with patient privacy. How can healthcare institutions maintain this balance effectively?
  6. Analyze the impact of emerging technologies like AI and IoT on medical privacy policies. How should regulations evolve to address these technological developments?
  7.  Evaluate the effectiveness of self-regulatory approaches to privacy protection in the healthcare sector. Under what conditions are they most successful?
  8. Compare medical privacy legislation across different countries or jurisdictions. What common principles exist, and what significant differences can be observed?
  9. Discuss the role of patient consent in the context of medical data sharing. How has the concept of consent evolved with digitization of health records?
  10.  Analyze the particular privacy challenges associated with genetic and genomic data. What special protections are needed for this type of information?

UNIT V Question

  1. Analyze the unique privacy challenges posed by the World Wide Web. How have these challenges evolved over time?
  2. Evaluate the protections provided by the Freedom of Information Act in the context of privacy. What are its strengths and limitations?
  3. Discuss the legal requirements for search warrants in the digital age. How do these requirements apply to digital evidence and online activities?
  4. Compare privacy protection approaches across different web-based services. What common strategies are employed and how effective are they?
  5. Analyze the role of user awareness and self-protection in maintaining privacy on the World Wide Web. What tools and techniques are available to individual users?
  6.  Evaluate the effectiveness of current browser privacy features and extensions. How do they protect users, and what limitations do they have?
  7. Discuss the tensions between freedom of information principles and privacy protection. How can these competing interests be balanced in policy and law?
  8. Analyze the evolution of search warrant requirements for digital content. How have courts interpreted the Fourth Amendment in the context of digital evidence?
  9. Compare different jurisdictional approaches to web privacy. How do regulatory frameworks like GDPR and CCPA differ in their protection models?
  10. Evaluate the role of data localization policies in protecting privacy. What are the implications of cross-border data transfers for individual privacy?

 

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