Research On Graph Structure Searchable Encryption Scheme Supporting Top-k Nearest Neighbor Keyword Search

With the rapid development and continuous innovation of cloud storage service technology in recent years,more and more digital device users are choosing to store their personal data on cloud storage servers.However,the unreliability of cloud servers can lead to security issues,such as data leaks.In order to solve these problems,encryption technology is widely used in cloud data storage.Specifically,users can use secure encryption methods to encrypt data and store it to a cloud server.Users can encrypt and decrypt data using a key,and the cloud server cannot know any plaintext data.Although encryption technology effectively protects the security of data,users need to download all data before decrypting it in order to find specific data.This process requires a lot of resources and time.As a result,searchable encryption(SE)technology has emerged as a necessary solution.Research on SE technology has been ongoing for a considerable amount of time.The SE technology enables users to search for cloud data by merely entering a few keywords,thereby facilitating efficient and secure data retrieval.The cloud server will return the search results to the user,who only needs to download the required data and decrypt it.During the entire process,the cloud server cannot access any clear text information.SE technology not only ensures data security,but also saves resources and time.However,due to the diversity of different data formats and usage environments,SE technology still faces some challenges.For example,how to search social network graphs,how to improve the accuracy of data search,and how to search for user-defined ranges of keywords.The focus of this article is to delve deeper into the searchable encryption of graph structures.The main research contents of this study are as follows:(1)Aiming at the problem of Top-k nearest neighbor keyword search in social network graphs,a secure index construction scheme based on keyword dictionary and a vertex distance index construction scheme are proposed,which can achieve Top-k nearest neighbor keyword search.The keyword dictionary returns all vertices containing the keywords entered by the user.The vertex distance dictionary determines the distance of each vertex,and returns the nearest k nodes to the user.Through experiments and analysis,this method solves the problem of Top k nearest neighbor keyword search in social network graphs.(2)Based on the proposed scheme,this article uses Redis cache and Springboot framework to build a prototype system of Top-k nearest neighbor keyword search.The system implements functions such as graph structure data encryption,Top-k nearest neighbor keyword search,and data decryption,meeting users’ needs for Top-k nearest neighbor keyword search in social network graphs.(3)Experimental testing was conducted using a real social network graph structure dataset,and the test results met the daily use needs of users.