In this paper, we present one method to attack on the GMR-2 algorithm used in satellite phone under the chosen-plaintexts. First using the relationship of the rows of the two s-boxes and outputs of the F coordinate, w...In this paper, we present one method to attack on the GMR-2 algorithm used in satellite phone under the chosen-plaintexts. First using the relationship of the rows of the two s-boxes and outputs of the F coordinate, we attack on the GMR-2 algorithm. Then we deduce the happening probability of read-collision, and analyze its mathematical expectation. Finally, combining with the read-collision, we present an improved method to attack on the GMR-2 algorithm. The research results show that the complexity of the improved algorithm is about 220, and the session key Kc can be recovered in about 0.3 seconds. Compared with the available method, our method takes less time than the guess-and-decide attack method which is 700 s.展开更多
In order to meet the actual operation demand of visual navigation during cotton field management period,image detection algorithm of visual navigation route during this period was investigated in this research.Firstly...In order to meet the actual operation demand of visual navigation during cotton field management period,image detection algorithm of visual navigation route during this period was investigated in this research.Firstly,for the operation images under natural environment,the approach of color component difference,which is applicable for cotton field management,was adopted to extract the target characteristics of different regions inside and outside cotton field.Secondly,the median filtering method was employed to eliminate noise in the images and realize smoothing process of the images.Then,according to the regional vertical cumulative distribution graph of the images,the boundary characteristic of the cotton seedling region was obtained and the central position of the cotton seedling row was determined.Finally,the detection of the candidate points cluster was realized,and the navigation route was extracted by Hough transformation passing the known point.The testing results showed that the algorithms could rapidly and accurately detect the navigation route during cotton field management period.And the average processing time periods for each frame image at the emergence,strong seedling,budding and blooming stages were 41.43 ms,67.83 ms,68.80 ms and 74.05 ms,respectively.The detection has the advantage of high accuracy,strong robustness and fast speed,and is simultaneously less vulnerable to interference from external environment,which satisfies the practical operation requirements of cotton field management machinery.展开更多
基金supported by China Scholarship Council under Grant No.201506965088
文摘In this paper, we present one method to attack on the GMR-2 algorithm used in satellite phone under the chosen-plaintexts. First using the relationship of the rows of the two s-boxes and outputs of the F coordinate, we attack on the GMR-2 algorithm. Then we deduce the happening probability of read-collision, and analyze its mathematical expectation. Finally, combining with the read-collision, we present an improved method to attack on the GMR-2 algorithm. The research results show that the complexity of the improved algorithm is about 220, and the session key Kc can be recovered in about 0.3 seconds. Compared with the available method, our method takes less time than the guess-and-decide attack method which is 700 s.
基金This work has been financially supported by the National Natural Science Foundation of China(Grant No.31071329)the Team Construction of Young and Middle-aged Talents in Science and Technology Innovation of Xinjiang Corps(Grant No.2016BC001)。
文摘In order to meet the actual operation demand of visual navigation during cotton field management period,image detection algorithm of visual navigation route during this period was investigated in this research.Firstly,for the operation images under natural environment,the approach of color component difference,which is applicable for cotton field management,was adopted to extract the target characteristics of different regions inside and outside cotton field.Secondly,the median filtering method was employed to eliminate noise in the images and realize smoothing process of the images.Then,according to the regional vertical cumulative distribution graph of the images,the boundary characteristic of the cotton seedling region was obtained and the central position of the cotton seedling row was determined.Finally,the detection of the candidate points cluster was realized,and the navigation route was extracted by Hough transformation passing the known point.The testing results showed that the algorithms could rapidly and accurately detect the navigation route during cotton field management period.And the average processing time periods for each frame image at the emergence,strong seedling,budding and blooming stages were 41.43 ms,67.83 ms,68.80 ms and 74.05 ms,respectively.The detection has the advantage of high accuracy,strong robustness and fast speed,and is simultaneously less vulnerable to interference from external environment,which satisfies the practical operation requirements of cotton field management machinery.
