• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.9
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• pp.55-64
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• 2012

Until now, Side Channel Attack has been known to be effective to crack decrypt key such as smart cards, electronic passports and e-ID card based on Chip. Combination of Masking and shuffling methods have been proposed practical countermeasure. Newly, S.Tillich suggests biased-mask using template attack(TA) to attack AES with masking and shuffling. However, an additional assumption that is acquired template information previously for masking value is necessary in order to apply this method. Moreover, this method needs to know exact time position of the target masking value for higher probability of success. In this paper, we suggest new practical method called Biasing Power Analysis(BPA) to find a secret key of AES based on masking-shuffling method. In BPA, we don't use time position and template information from masking value. Actually, we do experimental works of BPA attack to 128bit secret key of AES based on masking-shuffling method performed MSP430 Chip and we succeed in finding whole secret key. The results of this study will be utilized for next-generation ID cards to verify physical safety.

• IEMEK Journal of Embedded Systems and Applications
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• v.19 no.1
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• pp.19-25
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• 2024

This paper proposes an artificial intelligence-based personal information area object detection optimization method in an embedded system to de-identify personal information in video data. As an object detection optimization method, first, in order to increase the detection rate for personal information areas when detecting objects, a gyro sensor is used to collect the shooting angle of the image data when acquiring the image, and the image data is converted into a horizontal image through the collected shooting angle. Based on this, each learning model was created according to changes in the size of the image resolution of the learning data and changes in the learning method of the learning engine, and the effectiveness of the optimal learning model was selected and evaluated through an experimental method. As a de-identification method, a shuffling-based masking method was used, and double-key-based encryption of the masking information was used to prevent restoration by others. In order to reuse the original image, the original image could be restored through a security key. Through this, we were able to secure security for high personal information areas and improve usability through original image restoration. The research results of this paper are expected to contribute to industrial use of data without personal information leakage and to reducing the cost of personal information protection in industrial fields using video through de-identification of personal information areas included in video data.