Improving the Accuracy of the Intrusion Detection System in the Detection of DoS attack using Ada boosting and comparison with SVM

The goal of this research is to create a cutting-edge IDS that uses Ada Boosting (Group 2) and then compare it to a Support Vector Machine. (Group 1). The research incorporates two algorithms for two IDS groups namely Ada Boosting and SVM. There are 19 samples in each of two groups, for a total of 38 used in the analysis. SPSS was utilised for the statistical analysis. Using G power and a pretest power of 80%, the sample size was determined. The results show that the IDSs work well, with a significance level of p 0.05. Innovative Intrusion Detection System with Ada Boosting dramatically increases IDS accuracy with increasing percentages, and this improvement is statistically significant at the 0.0, or p 0.05 level. The Mean accuracy of Ada Boosting for (Group 2) is 0.994 and with SVM (Group 1) is 0.985. By comparing the performance of the Ada Boosting based IDS and SVM based IDS, Ada boosting based IDS significantly perform better.