- G(int[], double[]) - Static method in class bham.leakiest.Stats
-
Returns G value given observed counts and expected counts.
- gain(String[], String, Set<String>, String[]) - Method in class bham.leakiest.infotheory.GainFunction
-
Returns the gain of the attacker when a guess, an input
and a guess domain are given.
- GainFunction - Class in bham.leakiest.infotheory
-
This class represents a state.
- GainFunction(String) - Constructor for class bham.leakiest.infotheory.GainFunction
-
Constructs a gain function.
- generateChannel() - Method in class bham.leakiest.Observations
-
Returns the channel.
- gEntropy(double[], State[], GainFunction, Set<String>, String[]) - Static method in class bham.leakiest.infotheory.GLeakage
-
Calculates the g-entropy of a probability distribution.
- gEntropy(ProbDist, GainFunction, Set<String>) - Static method in class bham.leakiest.infotheory.GLeakage
-
Calculates the g-entropy of a probability distribution.
- getAcceptableError() - Method in class bham.leakiest.infotheory.BlahutArimoto
-
Returns the acceptable error of the result.
- getAllMarginals() - Method in class bham.leakiest.ProbDist
-
Returns all the marginals of this probability distribution.
- getBinomialCoefficient(int) - Method in class bham.leakiest.BinomialDist
-
Returns the binomial coefficient indexed by the number of samples and k.
- getCapacity(Observations) - Static method in class bham.leakiest.Estimate
-
Calculates the channel capacity from given observations.
- getCapacity() - Method in class bham.leakiest.infotheory.BlahutArimoto
-
Returns the capacity.
- getChannel() - Method in class bham.leakiest.ReadFile
-
Returns the channel.
- getChannelMatrix() - Method in class bham.leakiest.Observations
-
Gives the channel matrix.
- getCondMinEntropy(Observations) - Static method in class bham.leakiest.Estimate
-
Calculates the conditional min-entropy leakage from given observations.
- getCondMinEntropyLowerBound(Observations) - Static method in class bham.leakiest.Estimate
-
Calculates the lower bound of the confidence interval (95%)
of conditional min-entropy from a given chanel.
- getCondMinEntropyUpperBound(Observations) - Static method in class bham.leakiest.Estimate
-
Calculates the upper bound of the confidence interval (95%)
of conditional min-entropy from a given chanel.
- getContinuousData() - Method in class bham.leakiest.ReadFile
-
Returns continuous data.
- getCorrectedCapacity(Observations) - Static method in class bham.leakiest.Estimate
-
Calculates the corrected channel capacity from given observations.
- getCorrectedMIConfidenceIntervalUnderKnownPrior(Observations, ProbDist) - Static method in class bham.leakiest.Estimate
-
Calculates the confidence interval for corrected mutual information from
given observations
when the input distribution is also estimated from the sample.
- getCorrectedMILowerBoundUnderKnownPrior(Observations, ProbDist) - Static method in class bham.leakiest.Estimate
-
Calculates the lower bound of the confidence interval (95%)
of mutual information from given observations
when the input distribution is also estimated from the sample.
- getCorrectedMIUpperBoundUnderKnownPrior(Observations, ProbDist) - Static method in class bham.leakiest.Estimate
-
Calculates the upper bound of the confidence interval (95%)
of mutual information from given observations
when the input distribution is also estimated from the sample.
- getCorrectedMutualInformation(Observations) - Static method in class bham.leakiest.Estimate
-
Calculates the corrected mutual information from given observations.
- getCorrectedMutualInformationConfidenceInterval(Observations) - Static method in class bham.leakiest.Estimate
-
Calculates the confidence interval for corrected mutual information from
given observations
when the input distribution is also estimated from the sample.
- getCorrectedMutualInformationLowerBound(Observations) - Static method in class bham.leakiest.Estimate
-
Calculates the lower bound of the confidence interval (95%)
of mutual information from given observations
when the input distribution is also estimated from the sample.
- getCorrectedMutualInformationUpperBound(Observations) - Static method in class bham.leakiest.Estimate
-
Calculates the upper bound of the confidence interval (95%)
of mutual information from given observations
when the input distribution is also estimated from the sample.
- getCorrectedMutualInformationWithKnownPrior(Observations, ProbDist) - Static method in class bham.leakiest.Estimate
-
- getDegreeOfFreedomMI() - Method in class bham.leakiest.Observations
-
Gives the number of unique pairs of inputs and outputs encountered so far.
- getDistribution() - Method in class bham.leakiest.ReadFile
-
Returns the distribution.
- getElement1() - Method in class bham.leakiest.comparator.Pair
-
Returns the first element of the pair.
- getElement2() - Method in class bham.leakiest.comparator.Pair
-
Returns the second element of the pair.
- getFeatureIndices(TreeSet<Integer>, TreeSet<String>) - Method in class bham.leakiest.ARFFFile
-
Computes the a tree set of feature indices that appear in
the given string set.
- getGuessDomain() - Method in class bham.leakiest.ReadFile
-
Returns the set of all guesses.
- getInputDistYieldingCapacity(Observations) - Static method in class bham.leakiest.Estimate
-
Calculates the input distribution that gives the channel capacity.
- getInputNames() - Method in class bham.leakiest.Channel
-
- getInputNames() - Method in class bham.leakiest.Observations
-
Gives the array of input names.
- getInputObservationsArray() - Method in class bham.leakiest.Observations
-
Returns the array of numbers of input observations.
- getInputProbDist() - Method in class bham.leakiest.Observations
-
Returns the input probability distribution obtained from the observations.
- getIterationCount() - Method in class bham.leakiest.infotheory.BlahutArimoto
-
Returns the number of iterations in Blahut-Arimoto algorithm.
- getJointDist(ProbDist) - Method in class bham.leakiest.Channel
-
Return the joint distribution on inputs and outputs
generated by a given prior and this channel.
- getJointDist(ProbDist, Channel) - Static method in class bham.leakiest.Channel
-
Return the joint distribution on inputs and outputs generated by prior and channel.
- getMarginal(int) - Method in class bham.leakiest.ProbDist
-
Returns a marginal probability distribution.
- getMatrix() - Method in class bham.leakiest.Channel
-
Returns the channel matrix.
- getMaxInputDist() - Method in class bham.leakiest.infotheory.BlahutArimoto
-
Returns the input distribution that achieves capacity.
- getMean() - Method in class bham.leakiest.BinomialDist
-
Calculate the mean of the binomial distribution.
- getMinCapacity(Observations) - Static method in class bham.leakiest.Estimate
-
Calculates the min-capacity leakage from given observations.
- getMinEntropyLeak(Observations) - Static method in class bham.leakiest.Estimate
-
Calculates the min-entropy leakage from given observations.
- getMinEntropyLeakLowerBound(Observations) - Static method in class bham.leakiest.Estimate
-
Calculates the lower bound of the confidence interval (95%)
of min-entropy leakage from a given chanel.
- getMinEntropyLeakUpperBound(Observations) - Static method in class bham.leakiest.Estimate
-
Calculates the upper bound of the confidence interval (95%)
of min-entropy leakage from a given chanel.
- getMutualInformation(Observations) - Static method in class bham.leakiest.Estimate
-
Calculates the mutual information from given observations.
- getNameOfGainFunction() - Method in class bham.leakiest.infotheory.GainFunction
-
Returns the name of the gain function.
- getNoOfSamples() - Method in class bham.leakiest.BinomialDist
-
Returns the number of trials.
- getNumJoint() - Method in class bham.leakiest.ProbDist
-
Returns the number of elements in a joint input.
- getObservations() - Method in class bham.leakiest.ReadFile
-
Returns the observation.
- getObservationsMatrix() - Method in class bham.leakiest.Observations
-
Like getChannelMatrix(), but the cells contain the number of times the
respective input and output have been observed together.
- getObservationsMatrixMap() - Method in class bham.leakiest.Observations
-
Returns the hash map represetation of the observations matrix
in which each cell contains the number of times the
respective input and output have been observed together.
- getOutputNames() - Method in class bham.leakiest.Channel
-
- getOutputNames() - Method in class bham.leakiest.Observations
-
Gives the array of output names.
- getOutputObservationsArray() - Method in class bham.leakiest.Observations
-
Returns the array of numbers of output observations.
- getPMFArray() - Method in class bham.leakiest.ProbDist
-
Returns the array of the probabilities of this probability distribution.
- getPMFCollection() - Method in class bham.leakiest.ProbDist
-
Returns the collection of the probabilities of this probability distribution.
- getPossibleError() - Method in class bham.leakiest.infotheory.BlahutArimoto
-
Returns the possible error of the result.
- getPossibleErrorOfCapacity(Observations) - Static method in class bham.leakiest.Estimate
-
Calculates the input distribution that gives the channel capacity.
- getPosteriorProbDist(ProbDist) - Method in class bham.leakiest.Channel
-
- getProb() - Method in class bham.leakiest.BinomialDist
-
Returns success probability in each trial.
- getProb(String) - Method in class bham.leakiest.ProbDist
-
Returns the probability of the state in the probability distribution.
- getProb(State) - Method in class bham.leakiest.ProbDist
-
Returns the probability of the state in the probability distribution.
- getProjectedState(State, int) - Method in class bham.leakiest.ProbDist
-
Returns the string that denotes a projection of a given joint state.
- getSampleCount() - Method in class bham.leakiest.Observations
-
Gives the number of samples recorded by this Observations object so far.
- getSampleCountGivenInput() - Method in class bham.leakiest.Observations
-
Gives the numbers of samples that have a given input
recorded by this Observations object so far.
- getSampleCountGivenOutput() - Method in class bham.leakiest.Observations
-
Gives the numbers of samples that have a given output
recorded by this Observations object so far.
- getSamples() - Method in class bham.leakiest.ARFFFile
-
Returns the samples array.
- getSortedObservationsMatrix(String[], String[]) - Method in class bham.leakiest.Observations
-
Like getObservationsMatrix, but the cells are sorted according
the given arrays of input and output names.
- getStatesArray() - Method in class bham.leakiest.ProbDist
-
Returns the array of the states of this probability distribution.
- getStatesCollection() - Method in class bham.leakiest.ProbDist
-
Returns the collection of the states of this probability distribution.
- getStatesNum() - Method in class bham.leakiest.State
-
Returns the number of all variables in the state.
- getStdDev() - Method in class bham.leakiest.BinomialDist
-
Calculate the standard deviation of the binomial distribution.
- getStdScore(double) - Method in class bham.leakiest.BinomialDist
-
Calculate the standard score of the binomial distribution.
- getUniqueInputCount() - Method in class bham.leakiest.Observations
-
Gives the number of unique inputs encountered so far.
- getUniqueOutputCount() - Method in class bham.leakiest.Observations
-
Gives the number of unique outputs encountered so far.
- getUpperBoundForZeroLeakage(Observations) - Static method in class bham.leakiest.Estimate
-
Calculates the upper bound for zero leakage from given observations.
- getValue(String) - Method in class bham.leakiest.State
-
Returns the value of the variable in the state.
- getVariance() - Method in class bham.leakiest.BinomialDist
-
Calculate the variance of the binomial distribution.
- getVariance(Observations) - Static method in class bham.leakiest.Estimate
-
Calculates the variance of the estimated mutual information
from given observations
when the input distribution is also estimated from the sample.
- getVars() - Method in class bham.leakiest.State
-
Returns the list of all variable in the state.
- GLeakage - Class in bham.leakiest.infotheory
-
This is a library for calculating g-entropy, conditional g-entropy
and g-leakage, defined by Alvim et.
- GLeakage() - Constructor for class bham.leakiest.infotheory.GLeakage
-
- gLeakage(ProbDist, Channel, GainFunction, Set<String>) - Static method in class bham.leakiest.infotheory.GLeakage
-
Calculates the g-leakage from a channel
given an input probability distribution pd
given a probability distribution, a gain function gf,
and the set of all guesses guessDomain.