Graphical Patterning-Platform of Software Malfunction for Power Profile-based Side-Channel Analysis
Hyeongrae Kim, Jeonghun Cho, Daejin Park · 2019
Recently, many defects that are not detected in a software system have been found. This flaw is dangerous because the system cannot detect it even if it is attacked by a fault. To detect these defects, we have focused on the unique characteristic of the software system, the power consumption pattern. By comparing this unique normal operation pattern with the realtime operation pattern, we thought that we could fully detect the malfunction. This paper proposes 2-dimension graphical string patterning platform and matcher using side-channel analysis (SCA). We designed the monitoring block which is composed of matcher and pattern generator using Chipwhisperer that is open-source platform for SCA. The patterns are generated in run-time and compared with normal operation pattern. By this proposed method, we were enable to detect malfunction in runtime.