public Gene crossOver(Gene gene)
{
Gene Child = new Gene();
int seed = unchecked(DateTime.Now.Ticks.GetHashCode());
Random rnd = new Random(seed);
int place = rnd.Next(1, this.binString.Length - 1);
Child.binString = this.getStringFirstPart(place) + gene.getStringSecondPart(place);
return Child;
}
private void GA_Click(object sender, EventArgs e)
{
//num of population
int population = 50;
int iteration = 100;
double crossOverRate = 0.5 ;
double mutationRate = 0.1 ;
string file = @"GA" + tbMinSim.Text + DateTime.Now.ToString("HH_mm_ss") + ".csv";
System.IO.StreamWriter outputFile;
outputFile = new System.IO.StreamWriter(file, false);
decimal minSim = Convert.ToDecimal(tbMinSim.Text);
List<Gene> genes = new List<Gene>();
List<int> taintIds = new List<int>();
int totalBenign = 0;
for (int i = 0; i < simTable.Count; i++)
{
if (simTable[i].familyName == "Benign")
{
totalBenign++;
}
}
int numOfTaintTrait = simTable[0].similarity.Count;
//generate first generation
for(int i = 0 ; i < population ; i++)
{
int seed = unchecked(DateTime.Now.Ticks.GetHashCode());
Gene newGene = new Gene();
Random rnd = new Random(seed);
for (int j = 0; j < numOfTaintTrait; j++)
{
if ((taintTraitQuality[j + 1].numOfMalware - taintTraitQuality[j + 1].numOfBenign) < 10 || taintTraitQuality[j + 1].numOfBenign > 10)
{
newGene.binString += '0';
}
else
{
newGene.binString += rnd.Next(0, 2).ToString();
}
}
newGene.computeFitness(ref simTable, minSim, totalBenign);
genes.Add(newGene);
}
for(int i = 0 ; i < iteration ; i++)
{
genes.Sort((x, y) => x.fitness.CompareTo(y.fitness));
for(int k = 0 ; k < Convert.ToInt32(population*crossOverRate) ; k++ )
{
genes.RemoveAt(0);
}
int seed = unchecked(DateTime.Now.Ticks.GetHashCode());
Random rnd = new Random(seed);
while (genes.Count < population)
{
Gene newGene = new Gene();
int select1, select2;
select1 = rnd.Next(0, genes.Count);
select2 = rnd.Next(0, genes.Count);
while (select1 == select2)
{
select2 = rnd.Next(0, genes.Count);
}
newGene = genes[select1].crossOver(genes[select2]);
newGene.computeFitness(ref simTable, minSim, totalBenign);
genes.Add(newGene);
}
//for (int j = 0; j < genes.Count; j++ )
//{
// if (((float)rnd.Next(5000) / 5000) > mutationRate)
// {
// genes[j].mutation();
// genes[j].computeFitness(ref simTable, minSim, totalBenign);
// }
//}
genes.Sort((x, y) => y.fitness.CompareTo(x.fitness));
Console.WriteLine("tp:" + genes[0].tp.ToString() + " dRate :" + genes[0].dRate.ToString() + " fit:"+genes[0].fitness.ToString());
outputFile.WriteLine((i + 1).ToString() + "," + genes[0].fp.ToString() + "," + genes[0].tp.ToString() + "," + genes[0].dRate.ToString() + "," + genes[0].fitness.ToString());
}
genes.Sort((x, y) => y.tp.CompareTo(x.tp));
outputFile.WriteLine(genes[0].binString + ",1," + genes[0].fp.ToString() + "," + genes[0].tp.ToString() + "," + genes[0].dRate.ToString() + "," + genes[0].fitness.ToString());
outputFile.WriteLine(genes[1].binString + ",2," + genes[1].fp.ToString() + "," + genes[1].tp.ToString() + "," + genes[1].dRate.ToString() + "," + genes[1].fitness.ToString());
outputFile.WriteLine(genes[2].binString + ",3," + genes[2].fp.ToString() + "," + genes[2].tp.ToString() + "," + genes[2].dRate.ToString() + "," + genes[2].fitness.ToString());
outputFile.Close();
}
