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Glite Dictionary
👀 Impossible to distinguish 🗂️ Hidden differences
indiscernibility

indiscernibility

9.9
A property of data where people cannot be told apart by the shared information
  • noun
  • /ˌɪndɪˈsɜrnəˈbɪlɪti/
  • Specialized
translation icon : indiscernibilidad
  • To comply with regulations, the research team ensured indiscernibility among patients' records before publishing the dataset.

Examples

  • K-anonymity aims to achieve indiscernibility so attackers cannot re-identify individuals from quasi-identifiers.

  • The privacy officer measured indiscernibility across demographic fields to estimate disclosure risk for the release.

  • The indiscernibility of individuals in the dataset is crucial for privacy.

  • Researchers aim for indiscernibility to protect personal data.

  • To comply with regulations, the research team ensured indiscernibility among patients' records before publishing the dataset.

  • K-anonymity aims to achieve indiscernibility so attackers cannot re-identify individuals from quasi-identifiers.

  • The privacy officer measured indiscernibility across demographic fields to estimate the disclosure risk for the release.

Synonyms

indistinguishability
vsindiscernibility
9.9

A situation when you cannot tell two things apart

is limited to records made alike by specific released attributes in a dataset
indistinction
vsindiscernibility
8.6

Not clearly separate from something else

is a precise dataset property where many records share the same released attributes

Antonyms

discernability
7.5

How easy it is to see or tell things apart

How Identifiable

uniqueness
25 4.1
pseudonymity
1 9.9
anonymity
106 6.5
indiscernibility
  • Specialized
9.9

Surface Forms

indiscernibility singular
indiscernibilities plural

Morphology

indiscernibility = indiscernible (semi-transparent) = in + discern + ible + ity

The noun is a regular quality/state formation from the adjective 'indiscernible'.

Etymology

Indiscernibility comes from the parts in- meaning 'not' and discern meaning 'to tell apart', so it literally means 'not able to be told apart'. In data privacy it describes a dataset where people's records look the same under the released fields, so no one can pick out a person from the rest.