EVALUATING HOST-BASED INTRUSION DETECTION ON THE ADFA-WD AND ADFA-WD:SAA DATASETS
Charles-Elie Simon, Илья Владимирович Соченков · 2017
With the growth of the internet and technology also comes advancements in methods of cyber-attacks such as zero-day and stealth attacks, a more effective method of network safety is essential for network stability. This research paper will assess anomalous patterns of Normal Pattern and Abnormal Pattern comprised of system calls based on the Dynamic-Link Library. The two datasets are designed on Windows Operating System Host-based Intrusion Detection System; comprised of the ADFA-WD and ADFA-WD:SAA. The development of a binary feature space is discussed. Support Vector Machine classifier with sigmoid and RBF kernels is compared to the Random Forest classifier.