Abstract：Provenance dependency path patterns are the foundations of many provenance based cloud data security measures. This article analyzes the importance of provenance dependency path pattern mining in provenance based security system with a linearization algorithm for provenance graphs that enables grammar induction and parsing of provenance data using automata models. A similarity measurement method is given for dependency paths based on grammar parsing with a dependency path pattern mining algorithm to reduce reliance on the domain knowledge and support automatic provenance rule learning. The feasibility and effectiveness of the approach are demonstrated by experiments.
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