Abstract
With the continuous development of the Internet of things (IoTs), data security and privacy protection in the IoTs are becoming increasingly important. Aiming at the hugeness, redundancy, and heterogeneity of data in the IoTs, this paper proposes a ranked searchable encryption scheme based on an access tree. First, this solution introduces parameters such as the word position and word span into the calculation of the relevance score of keywords to build a more accurate document index. Secondly, this solution builds a semantic relationship graph based on mutual information to expand the query semantics, effectively improving the accuracy and recall rate during retrieval. Thirdly, the solution uses an access tree control structure to control user authority and realizes fine-grained access management to data by data owners in the IoTs. Finally, the safety analysis of this scheme and the efficiency comparison with other existing schemes are given.
Highlights
With the rapid development of Internet of things (IoTs) technology, it has been used in all walks of life and has been widely recognized in various fields such as medical care, smart transportation, government work, smart home, and environmental monitoring [1,2,3,4,5]
In view of this situation, the easiest way is to download all encrypted data locally and decrypt them one by one before searching. This method does not make full use of the computing power of the cloud server and wastes a lot of time and bandwidth power consumption, so that it cannot meet the actual needs of the cloud storage of the IoTs
The word position [26] refers to the area where a keyword appears in a document, which is of great value for judging the importance of the keyword
Summary
With the rapid development of IoTs technology, it has been used in all walks of life and has been widely recognized in various fields such as medical care, smart transportation, government work, smart home, and environmental monitoring [1,2,3,4,5]. The document vector is divided into blocks to effectively filter a large number of irrelevant documents, which effectively improves the efficiency of the scheme This solution does not involve access control and can only be limited to a single legitimate user’s query and is not suitable for the needs of keywords being queried by multiple users in an actual environment. (1) This paper introduces parameters such as word position and word span into the calculation of the relevance score of keywords and assigns more accurate weights to keywords at different positions in the document, thereby constructing a more accurate document index (2) This paper builds a semantic relationship graph based on mutual information to expand the query vector semantics, which effectively improves the precision and recall during retrieval (3) This paper involves multikeyword search and access control. Users whose attributes meet the access policy defined by the data owner can search encrypted data with multiple keywords, so as to realize the fine-grained access management of the data by the data owner in the IoTs
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