performed on the operable sub-part of the chromosome.

Based upon the chosen cross-over rate, the cross-over operation is performed. Two parent chromosomes are randomly selected from the population and a cross-over index is selected randomly. This index separates the operable chromosome into left and right portions in each parent. The right portions are then swapped between parents to form two new operable chromosomes. These child chromosomes are then inserted into the population. The cross-over operation is illustrated in Figure \[fig:f2\].

The mutation operation perturbs values of randomly selected cells based on a chosen mutation rate. The operation first randomly selects chromosomes to operate upon based on the mutation rate. Then, a mutation index is randomly selected. Using this index, the targeted chromosome is modified as shown in the example of Figure \[fig:f3\]. The resulting chromosome is left in the population in its modified form.

Upon completion of the cross-over and mutation operators, the chromosomes’ fitness functions are evaluated. In this domain, the fitness metric is the output probability that the chromosome is classified as benign by a machine learning classifier. To evaluate the chromosome, the operable chromosome must be recombined with the immutable part to form a valid chromosome. The 