Enhancing Technologies Flashcards

Which technique enables a researcher to determine whether a specific individual's data is in a dataset without the organization revealing the dataset contents?

Answer: Private information retrieval (PIR)

Private information retrieval (PIR) allows a user to query a database and retrieve a record without the database owner learning which record was accessed.

Format-preserving encryption (FPE) is preferred over standard encryption in some data systems because:

Answer: It produces ciphertext in the same format as plaintext, minimizing application changes

FPE maintains the format (length, character set) of the original data, allowing encrypted values to pass validation rules and minimizing changes to downstream systems.

In the context of PETs, what is 'data vault tokenization' primarily designed to protect against?

Answer: Exposure of sensitive data in case of a breach by storing tokens instead of real values in application systems

Data vault tokenization ensures that even if the application database is breached, attackers only obtain tokens with no value outside the secure vault, limiting breach impact.

Which emerging privacy-enhancing technology uses cryptographic commitments to allow auditors to verify data processing compliance without accessing the underlying data?

Answer: Zero-knowledge proofs

Zero-knowledge proofs allow a party to prove that a computation was performed correctly or that data meets certain criteria without revealing the actual data to the verifier.

A financial services firm wants to analyze transaction patterns across multiple banks without any bank revealing its customers' individual transactions to the others. The most appropriate PET is:

Answer: Secure multi-party computation (SMPC)

SMPC allows multiple banks to jointly compute analytics on their combined data without any party ever seeing another party's raw transaction records.

The 't-closeness' model extends l-diversity by requiring that:

Answer: The distribution of sensitive attributes within each group closely matches the distribution in the overall dataset

T-closeness requires the distribution of sensitive values in any equivalence class to be no further than a threshold t from the overall dataset distribution, preventing skewness attacks.

Which of the following is the MOST significant privacy challenge when deploying large language models (LLMs) trained on personal data?

Answer: LLMs may memorize and reproduce training data containing personal information upon prompting

Research has demonstrated that LLMs can memorize verbatim sequences from training data, meaning personal information could be extracted through targeted prompts.