DPDP 면접 질문과 답변
Ques 11. Explain the concept of 'Privacy Impact Assessment' (PIA) and its significance.
PIA is a process to assess and mitigate the privacy risks associated with a project or system. It helps organizations identify and address potential privacy issues before they become problems, ensuring compliance with data protection regulations.
Example:
Conducting a PIA before launching a new customer data management system helps in identifying and addressing potential privacy risks.
Ques 12. What is the difference between confidentiality, integrity, and availability in the context of data protection?
Confidentiality ensures that data is only accessible to authorized individuals. Integrity ensures that data is accurate and unaltered, while availability ensures that data is accessible when needed.
Example:
Encrypting sensitive customer data (confidentiality) and implementing error-checking mechanisms (integrity) are measures that contribute to data protection.
Ques 13. Explain the principle of 'Purpose Limitation' in DPDP.
Purpose Limitation dictates that personal data should only be collected for specific, explicit, and legitimate purposes. Data controllers should not process data in ways incompatible with the initial purposes.
Example:
If an online survey collects customer feedback and explicitly states that the data will only be used for improving services, it adheres to the principle of Purpose Limitation.
Ques 14. What is the role of consent in data processing, and how can organizations obtain valid consent?
Consent is permission from the data subject to process their personal data. To be valid, consent must be freely given, specific, informed, and unambiguous. Organizations should provide clear opt-in mechanisms and allow easy withdrawal of consent.
Example:
A website asking users to check a box to agree to the terms of service and data processing is seeking consent.
Ques 15. How does the principle of 'Accountability' contribute to data protection practices?
Accountability requires organizations to be responsible for complying with data protection regulations. It involves maintaining records of processing activities, implementing data protection policies, and demonstrating compliance to authorities.
Example:
An organization regularly auditing its data protection practices and maintaining documentation of data processing activities demonstrates accountability.
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