| Summary: | Side-Channel Attack (SCA) are attacks on cryptographic devices that extracts its critical and sensitive data. This attack exploits information leaked by the hardware of the device which disregards the software defenses of the targeted device. In this study, we implement Image Edge Detection in efforts to improve efficiency of SCA. Edge detection is an important tool in digital image processing applications as it can extract critical information from the image. Sobel operator-based algorithm creates an image which highlights edges and transitions. In real-time image processing applications, speed of image processing is a major concern. This is due to the huge data pixels needed to be processed within the time constraint given. However, reconfigurable device such as FPGA deploys parallelism methods in processing algorithms, which reduces execution times and increase operation speed. In this project, Xilinx ZYNQ FPGA Board is provided. The efficiency of SCA is greatly influenced by detection of the power model which correlates to the power consumption of the board. Therefore, in this project, Morphological Image Processing is utilized to identify suitable Power Model for the attack.
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