DPDP Questions et reponses d'entretien
Question 21. Explain the concept of 'Data Breach' and the steps organizations should take in response.
A data breach is an unauthorized access or disclosure of sensitive data. Organizations should respond by identifying and containing the breach, notifying affected individuals and relevant authorities, and taking measures to prevent future breaches.
Example:
If a hacker gains access to customer records in an online database, it constitutes a data breach.
Question 22. What is the significance of 'Data Encryption' in ensuring data security?
Data encryption transforms data into a secure format, making it unreadable without the correct decryption key. It is crucial for protecting sensitive information during transmission and storage, adding an extra layer of security.
Example:
Using HTTPS (encrypted) instead of HTTP (unencrypted) for transmitting sensitive data over the internet ensures data encryption.
Question 23. Explain the role of 'Data Protection Authorities' (DPAs) and their powers.
Data Protection Authorities are regulatory bodies responsible for enforcing data protection laws. They have the power to investigate, issue fines for non-compliance, and provide guidance on data protection matters. DPAs play a crucial role in ensuring organizations adhere to data protection regulations.
Example:
If a company is suspected of mishandling personal data, the DPA may conduct an investigation and impose fines if violations are found.
Question 24. What is the 'Privacy Shield' framework, and how does it facilitate data transfers between the EU and the U.S.?
Privacy Shield was a framework for data transfers between the EU and the U.S., ensuring that companies met certain privacy standards. It was invalidated, but its principles influenced subsequent agreements. Privacy Shield aimed to protect the privacy rights of EU individuals whose data was transferred to the U.S.
Example:
A European company transferring customer data to a U.S.-based cloud service provider would ensure Privacy Shield compliance (before its invalidation) to meet data protection standards.
Question 25. What are the ethical considerations in AI and machine learning applications that involve personal data?
Ethical considerations include transparency, fairness, and preventing bias in AI algorithms. Organizations should ensure that AI systems do not discriminate against individuals based on protected characteristics and should be transparent about how AI decisions are made.
Example:
An AI-driven hiring system should be designed to avoid bias and ensure fair treatment of all candidates, regardless of demographic factors.
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