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G

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.
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