Results for classifiers learnt from 20 initial configurations. ======== TABLE II ======== model type accuracy cross-validation sensitivity specificity SVM-linear 52.09% 50.04% 62.18% 42.03% SVM-polynomial 58.08% 51.01% 61.68% 54.48% SVM-RBF 95.73% 94.77% 99.78% 91.68% ========= TABLE III ========= number of mutants effective mutants accuracy cross-validation 300 32 85.75% 81.01% 400 52 90.11% 89.98% 500 71 94.01% 95.04% 600 91 95.73% 95.09% 700 109 95.73% 94.77% ======== TABLE IV ======== #time interval accuracy cross-validation 100 94.54% 93.25% 150 94.14% 92.14% 200 95.79% 94.45% 250 95.73% 94.77% 300 94.98% 94.31% ======= TABLE V ======= attack # detected accuracy 1 yes 90.16% 2 yes 94.09% 3 yes 71.11% 4 yes 98.14% 5 yes 95.12% 6 yes 91.09% 7 yes 76.98% 8 yes 94.14% 9 yes 95.52% 10 yes 99.11% 11 yes 90.19% 12 yes 95.16% 13 yes 98.97% 14 yes 95.47% 15 yes 94.79% ======== TABLE VI ======== attack stage # effective mutants # detected accuracy (detected) accuracy (all) PLC1 8 5 99.18% 74.84% PLC3 20 17 98.19% 91.92% PLC4 5 4 99.09% 90.09% PLC5 2 2 98.13% 98.13% PLC6 5 5 98.97% 99.97% summary 40 33 98.41% 90.09%