A Fast Kernel on Hierarchial Tree Structures and Its Application to Windows Application Behavior Analysis

Abstract

System calls have been proved to be important evidence for analyzing the behavior of running applications. However, application behavior analyzers which investigate the majority of system calls usually suffer from severe system performance deterioration or frequent system crashes. In the presented study, a light weighted analyzer is approached by two avenues. On the one hand, the computation load to monitor the system calls are considerably reduced by limiting the target functions to two specific groups: file accesses and Windows Registry accesses. On the other hand, analytical accuracy is achieved by deep inspection into the string parameters of the function calls, where the proximity of the programs are evaluated by the newly proposed kernel functions. The efficacy of the proposed approach is evaluated on real world datasets with promising results reported.