static void Main(string[] args)
{
//Generate the training data
int keySize = 64;
int messageSize = 64;
int trainingSetSize = 100;
List <Triplet> trainingSet = GenerateDESDataset(trainingSetSize, keySize, messageSize);
double[][] inputTraining, outputTraining;
Triplet.Transform2IO(trainingSet, out inputTraining, out outputTraining);
//Generate the test data
List <Triplet> testSet = GenerateDESDataset(trainingSetSize, keySize, messageSize);
double[][] inputTest, outputTest;
Triplet.Transform2IO(testSet, out inputTest, out outputTest);
//Find the right sizes, not sure why I have to do that :-/
int inputSize = trainingSet.First().original.Count() + trainingSet.First().encrypted.Count();
int outputSize = trainingSet.First().key.Count();
//Create a network
var function = new SigmoidFunction(2.0);
//ActivationNetwork network = new ActivationNetwork(function, inputSize, 25, outputSize);
//ParallelResilientBackpropagationLearning teacher = new ParallelResilientBackpropagationLearning(network);
DeepBeliefNetwork network = new DeepBeliefNetwork(inputSize, 10, outputSize);
Accord.Neuro.Learning.DeepNeuralNetworkLearning teacher = new DeepNeuralNetworkLearning(network);
//Train the network
int epoch = 0;
double stopError = 0.1;
int resets = 0;
double minimumErrorReached = double.PositiveInfinity;
while (minimumErrorReached > stopError && resets < 1)
{
network.Randomize();
//teacher.Reset(0.0125);
double errorTrain = double.PositiveInfinity;
for (epoch = 0; epoch < 500000 && errorTrain > stopError; epoch++)
{
errorTrain = teacher.RunEpoch(inputTraining, outputTraining) / (double)trainingSetSize;
//Console.WriteLine("Epoch " + epoch + " = \t" + error);
if (errorTrain < minimumErrorReached)
{
minimumErrorReached = errorTrain;
network.Save("cryptoDESNetwork.mlp");
}
Console.Clear();
Console.WriteLine("Epoch : " + epoch);
Console.WriteLine("Train Set Error : " + errorTrain.ToString("N2"));
double errorTest = teacher.ComputeError(inputTest, outputTest) / (double)inputTest.Count();
Console.WriteLine("Test Set Error : " + errorTest.ToString("N2"));
}
//Console.Write("Reset (" + error+")->");
resets++;
}
Console.WriteLine();
//Compute the reall error
foreach (Triplet tReal in testSet)
{
double[] rIn, rOut, pOut;
byte[] brMsg, brEncrypted, brKey;
tReal.ToBytes(out brMsg, out brEncrypted, out brKey);
tReal.ToIO(out rIn, out rOut);
pOut = network.Compute(rIn);
Triplet tPredicted = new Triplet(rIn, pOut, messageSize);
byte[] bpMsg, bpEncrypted, bpKey;
tPredicted.ToBytes(out bpMsg, out bpEncrypted, out bpKey);
int wrongBytes = 0;
for (int i = 0; i < keySize / 8; i++)
{
if (brKey[i] != bpKey[i])
{
wrongBytes++;
}
}
Console.WriteLine("Wrong bytes = " + wrongBytes);
//Console.WriteLine("REAL = \n" + tReal.GetBytesForm());
//Console.WriteLine("Predicted = \n" + tPredicted.GetBytesForm());
}
Console.ReadKey();
}
