Chosen-message pair Simple Power Analysis (SPA) attacks were proposed by Boer, Yen and Homma, and are attack methods based on searches for collisions of modular multiplication. However, searching for collisions is dif...Chosen-message pair Simple Power Analysis (SPA) attacks were proposed by Boer, Yen and Homma, and are attack methods based on searches for collisions of modular multiplication. However, searching for collisions is difficult in real environments. To circumvent this problem, we propose the Simple Power Clustering Attack (SPCA), which can automatically identify the modular multiplication collision. The insignificant effects of collision attacks were validated in an Application Specific Integrated Circuit (ASIC) environment. After treatment with SPCA, the automatic secret key recognition rate increased to 99%.展开更多
The main methods of the second phase quantitative analysis in current material science researches are manual recognition and extracting by using software such as Image Tool and Nano Measurer. The weaknesses such as hi...The main methods of the second phase quantitative analysis in current material science researches are manual recognition and extracting by using software such as Image Tool and Nano Measurer. The weaknesses such as high labor intensity and low accuracy statistic results exist in these methods. In order to overcome the shortcomings of the current methods, the Ω phase in A1-Cu-Mg-Ag alloy is taken as the research object and an algorithm based on the digital image processing and pattern recognition is proposed and implemented to do the A1 alloy TEM （transmission electron microscope） digital images process and recognize and extract the information of the second phase in the result image automatically. The top-hat transformation of the mathematical morphology, as well as several imaging processing technologies has been used in the proposed algorithm. Thereinto, top-hat transformation is used for elimination of asymmetric illumination and doing Multi-layer filtering to segment Ω phase in the TEM image. The testing results are satisfied, which indicate that the Ω phase with unclear boundary or small size can be recognized by using this method. The omission of these two kinds of Ω phase can be avoided or significantly reduced. More Ω phases would be recognized （growing rate minimum to 2% and maximum to 400% in samples）, accuracy of recognition and statistics results would be greatly improved by using this method. And the manual error can be eliminated. The procedure recognizing and making quantitative analysis of information in this method is automatically completed by the software. It can process one image, including recognition and quantitative analysis in 30 min, but the manual method such as using Image Tool or Nano Measurer need 2 h or more. The labor intensity is effectively reduced and the working efficiency is greatly improved.展开更多
基金supported in part by the National Natural Science Foundation of China under Grant No. 60873216Scientific and Technological Research Priority Projects of Sichuan Province under Grant No. 2012GZ0017Basic Research of Application Fund Project of Sichuan Province under Grant No. 2011JY0100
文摘Chosen-message pair Simple Power Analysis (SPA) attacks were proposed by Boer, Yen and Homma, and are attack methods based on searches for collisions of modular multiplication. However, searching for collisions is difficult in real environments. To circumvent this problem, we propose the Simple Power Clustering Attack (SPCA), which can automatically identify the modular multiplication collision. The insignificant effects of collision attacks were validated in an Application Specific Integrated Circuit (ASIC) environment. After treatment with SPCA, the automatic secret key recognition rate increased to 99%.
基金Project(51171209)supported by the National Natural Science Foundation of China
文摘The main methods of the second phase quantitative analysis in current material science researches are manual recognition and extracting by using software such as Image Tool and Nano Measurer. The weaknesses such as high labor intensity and low accuracy statistic results exist in these methods. In order to overcome the shortcomings of the current methods, the Ω phase in A1-Cu-Mg-Ag alloy is taken as the research object and an algorithm based on the digital image processing and pattern recognition is proposed and implemented to do the A1 alloy TEM （transmission electron microscope） digital images process and recognize and extract the information of the second phase in the result image automatically. The top-hat transformation of the mathematical morphology, as well as several imaging processing technologies has been used in the proposed algorithm. Thereinto, top-hat transformation is used for elimination of asymmetric illumination and doing Multi-layer filtering to segment Ω phase in the TEM image. The testing results are satisfied, which indicate that the Ω phase with unclear boundary or small size can be recognized by using this method. The omission of these two kinds of Ω phase can be avoided or significantly reduced. More Ω phases would be recognized （growing rate minimum to 2% and maximum to 400% in samples）, accuracy of recognition and statistics results would be greatly improved by using this method. And the manual error can be eliminated. The procedure recognizing and making quantitative analysis of information in this method is automatically completed by the software. It can process one image, including recognition and quantitative analysis in 30 min, but the manual method such as using Image Tool or Nano Measurer need 2 h or more. The labor intensity is effectively reduced and the working efficiency is greatly improved.
