The exponential growth of graph databases in recent decades has led to a wide range of applications for subgraph mining. Large dynamic graph databases can make it challenging to mine subgraph patterns since graph operations, such as subgraph isomorphism testing, are typically more costly, time-consuming, and memory-intensive than the A workable approach that is scalable, secure, and high-quality of service is still needed for subgraph mining. Addressing the present issues with query service authentication, graph indexing, subgraph searching, and graph data scalability is the aim of the proposed study in this work. In this paper, a novel PG-Sim Index technique has been introduced, which enables authenticated search for similarity subgraph queries based on distance-based indexing. The proposed work creates an efficient authentication-friendly static graph index for efficient authenticated search. This work is assessed using the AIDS Antiviral Screening Dataset and compared to various graph indexing techniques, including GMTree, DISR index, and ML Index, that make similarity search easier. The experimental findings for this novel index show high performance output in terms of the following metrics: mining accuracy, query response time, and query search authentication time. The results show that the proposed module performs 98% better overall at 100 ms when compared to existing systems.