static void ValidateModel(MarkovChain model, Dictionary <string, double> passwords, int guesses, bool hashed) //passwords here is not used...
{
Console.Write("Validating on {0} guesses... ", guesses);
PasswordCrackingEvaluator eval = new PasswordCrackingEvaluator(guesses, hashed);
var results = eval.Validate(model);
Console.WriteLine("Accounts: {0} Uniques: {1}", results._fitness, results._alternativeFitness);
}
// Runs a comparison of the two model types.
static void RunAllMarkovModelPairs(object special)
{
const string EXPERIMENT_OFFSET = @"..\..\..\experiments\intermediate\";
string[] models = new string[]
{
"first-order",
"8-layer"
};
// For every dataset, create a model
for (int i = 0; i < _datasetFilenames.Length; i++)
{
if (i != (int)special)
{
continue;
}
for (int m = 0; m < 2; m++)
{
int outputs;
string seedFile = EXPERIMENT_OFFSET + "seed-" + models[m] + "-" + _datasetFilenames[i].Name + ".xml";
Console.Write("Building {0} Markov model...", models[m]);
if (m == 0)
{
outputs = MarkovFilterCreator.GenerateFirstOrderMarkovFilter(seedFile, _passwords[i]);
}
else
{
outputs = MarkovFilterCreator.GenerateLayeredMarkovFilter(seedFile, _passwords[i], 8);
}
Console.WriteLine("Done! Outputs: {0}", outputs);
_experiment.OutputCount = outputs;
Console.WriteLine("Loading seed...");
var seed = _experiment.LoadPopulation(XmlReader.Create(seedFile))[0];
Console.WriteLine("Creating model...");
var model = _experiment.CreateGenomeDecoder().Decode(seed);
// For every dataset, test the model
for (int j = 0; j < _datasetFilenames.Length; j++)
{
Console.Write("Validating {0} {1} model on {2} with {3} guesses... ", models[m], _datasetFilenames[i].Name, _datasetFilenames[j].Name, VALIDATION_GUESSES);
PasswordCrackingEvaluator eval = new PasswordCrackingEvaluator(VALIDATION_GUESSES, false);
var results = eval.Validate(model, _passwords[j], EXPERIMENT_OFFSET + models[m] + "-" + _datasetFilenames[i].Name + "-" + _datasetFilenames[j].Name + ".csv", 10000);
// Console.WriteLine("Accounts: {0} Uniques: {1}", results._fitness, results._alternativeFitness);
Console.WriteLine("Total Score: {0} Uniques: {1}", results._fitness, results._alternativeFitness);
lock (_writerLock)
using (TextWriter writer = new StreamWriter(@"..\..\..\experiments\summary_results.csv", true))
writer.WriteLine("{0},{1},{2},{3},{4}%,{5}%",
_datasetFilenames[i].Name,
_datasetFilenames[j].Name,
results._fitness,
results._alternativeFitness,
results._fitness / (double)_passwords[j].Sum(kv => kv.Value) * 100,
results._alternativeFitness / (double)_passwords[j].Count * 100);
}
}
}
}
