Class/Object

ksb.csle.didentification.verification.check

ProbLDiversityCheck

Related Docs: object ProbLDiversityCheck | package check

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class ProbLDiversityCheck extends BaseLDiversityCheck

This class checks whether the anonymized data satisfies the probabilistic L-diversity constraint. Note that this class checks the l-diversity value in an single equivalence class, not the dataframe.

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BaseLDiversityCheck, AnyRef, Any
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Instance Constructors

  1. new ProbLDiversityCheck()

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Value Members

  1. final def !=(arg0: Any): Boolean

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  2. final def ##(): Int

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  3. final def ==(arg0: Any): Boolean

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  4. final def asInstanceOf[T0]: T0

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  5. def clone(): AnyRef

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  6. final def eq(arg0: AnyRef): Boolean

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  7. def equals(arg0: Any): Boolean

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  8. def finalize(): Unit

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    @throws( classOf[java.lang.Throwable] )
  9. final def getClass(): Class[_]

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  10. def getLDiversityValue(eqTable: Map[List[Any], Long]): Double

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    The probabilistic L-diversity method checks the probability of the most frequent attribute values in the equivalence class to be less than 1/l.

    The probabilistic L-diversity method checks the probability of the most frequent attribute values in the equivalence class to be less than 1/l. The table is said to be probabilistic l-diverse if every equivalence satisfy the probabilistic l-diverse.

    returns

    Boolean return true when satisfying privacy policy

    Definition Classes
    ProbLDiversityCheckBaseLDiversityCheck
  11. def getLDiversityValue(src: DataFrame, columnNames: Array[String], sens: Array[String]): Double

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    The common L-diversity method just checks whether the number of sensitive attributes is greater than given L-constraints.

    The common L-diversity method just checks whether the number of sensitive attributes is greater than given L-constraints. Generally, an equivalence class is l-diverse if contains at least 'l' well-represented values for the sensitive attribute. A table is l-diverse if every equivalence is l-diverse

    src

    The anonymized dataframe

    returns

    Double return the l-diversity value

    Definition Classes
    BaseLDiversityCheck
  12. def hashCode(): Int

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  13. final def isInstanceOf[T0]: Boolean

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  14. def lDiversityCheck(src: DataFrame, columnNames: Array[String], sens: Array[String], lDiversityValue: Double): Boolean

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    Checks the anonymized dataframe satisfies the given l-Diversity constraint.

    Checks the anonymized dataframe satisfies the given l-Diversity constraint.

    src

    The anonymized dataframe

    lDiversityValue

    the given l-diversity constraint

    returns

    Boolean return true if satisfying the given l-diversity constraint

    Definition Classes
    BaseLDiversityCheck
  15. final def ne(arg0: AnyRef): Boolean

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  16. final def notify(): Unit

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  17. final def notifyAll(): Unit

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  18. final def synchronized[T0](arg0: ⇒ T0): T0

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  19. def toString(): String

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  20. final def wait(): Unit

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  21. final def wait(arg0: Long, arg1: Int): Unit

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  22. final def wait(arg0: Long): Unit

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Inherited from BaseLDiversityCheck

Inherited from AnyRef

Inherited from Any

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