Efficient distributed zero-knowledge proof method based on Spark
A zero-knowledge proof and distributed technology, applied in the information field, can solve problems such as inability to handle large-scale calculations, limited single-machine memory, and long time, and achieve the effects of high degree of distribution, small memory dependence, and improved efficiency
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[0023] refer to figure 2 As shown, the present invention includes two types of distributed algorithm components: distributed merkle tree algorithm and distributed polynomial algorithm. SparkRDD key-value pairs are used to represent merkle trees, polynomials, and the evaluation results of polynomials at all points on a finite field. Merkle trees are represented as RDD([(node index, node value)]), polynomial f(X) The representation is RDD([(the exponent of X, the coefficient of this term)]), and the representation of the polynomial evaluation result is RDD([(the value of the X coordinate, the value of the polynomial at this point)]). Next, the specific implementation of various distributed algorithms is introduced.
[0024] Algorithm 1. The specific implementation of the merkle tree construction in the distributed merkle tree algorithm is as follows:
[0025] a) The input is an RDD composed of leaf nodes;
[0026] b) Traverse the RDD and convert the original (key, value) ...
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