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A good disturbance vector is one of the key techniques to find SHA-1 collisions and to construct valid differential paths. The main work of this paper is to classify the types of the optimal disturbance vectors.First, we improve the EEM disturbance vectors search algorithm by Manuel. We increase the Hamming weight of information window from 4 to 6, with 244 time complexity, which is 28 times better than that of Manuel’s work. Based on this result, we prove that there are only two types of the optimal disturbance vectors, type-I and type-II, which have minimum weight of 25 in the last 60 of the 80 expanded words, in the total 2512 disturbance vectors searching space.
A good disturbance vector is one of the key techniques to find SHA-1 collisions and to construct valid differential paths. The main work of this paper is to classify the types of the optimal disturbance vectors. First, we improve the EEM by Manuel. We increase the Hamming weight of information window from 4 to 6, with 244 time complexity, which is 28 times better than that of Manuel’s work. Based on this result, we prove that there are only two types of the optimal disturbance vectors , type-I and type-II, which have minimum weight of 25 in the last 60 of 80 expanded words, in the total 2512 disturbance vectors searching space.