有向图哈希
Directed Graph Hashing
AI总结：
针对有向图哈希研究空白，本文提出多种有向图哈希算法，含可处理环的Merkle风格递归哈希算法，能为对称节点分配相同哈希，可拓展至超图等复杂结构。
摘要：
本文提出了多种用于有向图哈希的算法，这些算法既可以对整张图进行哈希计算，也能为给定图中的特定节点分配哈希值。研究通过计算顶点轨道与图自同构群，对节点对称性的概念给出了精确定义，对称等价的节点会被分配相同的哈希值。本文还提出了一种新颖的Merkle风格哈希算法，该算法遵循递归原则：节点的哈希值应仅取决于其邻居节点的哈希值，且即便图中存在环也能正常运行，这是朴素方法无法实现的。结构化树哈希已在区块链、源代码版本控制及Web应用中得到广泛应用，但尽管树哈希十分普及，有向图哈希在现有文献中仍未被研究。本文提出的算法为有向图以及可归约为有向图的更复杂数据结构（如超图）的哈希计算开辟了新的可能。
英文摘要：
This paper presents several algorithms for hashing directed graphs. The algorithms given are capable of hashing entire graphs as well as assigning hash values to specific nodes in a given graph. The notion of node symmetry is made precise via computation of vertex orbits and the graph automorphism group, and nodes that are symmetrically identical are assigned equal hashes. We also present a novel Merkle-style hashing algorithm that seeks to fulfill the recursive principle that a hash of a node should depend only on the hash of its neighbors. This algorithm works even in the presence of cycles, which would not be possible with a naive approach. Structurally hashing trees has seen widespread use in blockchain, source code version control, and web applications. Despite the popularity of tree hashing, directed graph hashing remains unstudied in the literature. Our algorithms open new possibilities to hashing both directed graphs and more complex data structures that can be reduced to directed graphs such as hypergraphs.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
