def AdaptiveAttackShuffleDefense():
#Corresponding tag for saving files
#First part indicates the type of defense, second part indidcates the synthetic model and last part indicates the strenght of the attack (100%)
saveTag = "ViT-L-16, ViT-32(ImageNet21K), p100"
device = torch.device("cuda")
#Attack parameters
numAttackSamples = 1000
epsForAttacks = 0.031
clipMin = 0.0
clipMax = 1.0
#Parameters of training the synthetic model
imgSize = 224
batchSize = 32
numClasses = 10
numIterations = 4
epochsPerIteration = 10
epsForAug = 0.1 #when generating synthetic data, this value is eps for FGSM used to generate synthetic data
learningRate = (3e-2) / 2 #Learning rate of the synthetic model
#Load the training dataset, validation dataset and the defense
valLoader, defense = LoadShuffleDefenseAndCIFAR10()
trainLoader = DMP.GetCIFAR10Training(imgSize, batchSize)
#Get the clean data
xTest, yTest = DMP.DataLoaderToTensor(valLoader)
cleanLoader = DMP.GetCorrectlyIdentifiedSamplesBalancedDefense(
defense, numAttackSamples, valLoader, numClasses)
#Create the synthetic model
syntheticDir = "Models//imagenet21k_ViT-B_32.npz"
config = CONFIGS["ViT-B_32"]
syntheticModel = VisionTransformer(config,
imgSize,
zero_head=True,
num_classes=numClasses)
syntheticModel.load_from(numpy.load(syntheticDir))
syntheticModel.to(device)
#Do the attack
oracle = defense
dataLoaderForTraining = trainLoader
optimizerName = "sgd"
#Last line does the attack
AttackWrappersAdaptiveBlackBox.AdaptiveAttack(
saveTag, device, oracle, syntheticModel, numIterations,
epochsPerIteration, epsForAug, learningRate, optimizerName,
dataLoaderForTraining, cleanLoader, numClasses, epsForAttacks, clipMin,
clipMax)
def RaySAttackShuffleDefense():
#Load the model and dataset
valLoader, defense = LoadShuffleDefenseAndCIFAR10()
#Get the clean samples
numClasses = 10
attackSampleNum = 1000
cleanLoader = DMP.GetCorrectlyIdentifiedSamplesBalancedDefense(
defense, attackSampleNum, valLoader, numClasses)
#Set the attack parameters
epsMax = 0.031
queryLimit = 10000
#The next line does the actual attack on the defense
advLoader = AttackWrappersRayS.RaySAttack(defense, epsMax, queryLimit,
cleanLoader)
#Check the results
robustAcc = defense.validateD(advLoader)
cleanAcc = defense.validateD(valLoader)
#Print the results
print("Queries used:", queryLimit)
print("Robust acc:", robustAcc)
print("Clean acc:", cleanAcc)