Research On Encryption Schemes Supporting Non Precise Keyword Search

Due to the flexibility,reliability,and cheapness of cloud services,the cloud-based outsourcing model has become an important way for organizations and individuals to store and calculate data.However,in the current cloud environment,data lacks effective supervision and control,and user privacy is difficult to be guaranteed.At this time,various privacy-preserving computing technologies came into being.Searchable encryption is a cryptographic primitive that supports keyword retrieval of ciphertexts by cloud storage systems under the premise of ensuring data confidentiality.The traditional searchable encryption technology can only achieve precise keyword search,that is,when the keyword searched by the user is exactly the same as the preset keyword,the matching is successful.In response to this problem,scholars proposed wildcard searchable encryption and fuzzy searchable encryption to achieve non-precise keyword retrieval on the ciphertext.This thesis focuses on wildcard searchable encryption and fuzzy searchable encryption technology,and proposes the following two schemes:1.Verifiable wildcard searchable encryption without false positive.The scheme uses coding technology to convert prefix search,an important search form of wildcard search,into range search,and uses order-preserving encryption to ensure the consistency of the order of plaintext and ciphertext.In this way,the plaintext dictionary intervals for the keyword given the first one or more characters is corresponding to the definite ciphertext value range,and the search results without false positives are realized.Furthermore,an Ordered Binary Bitmap Tree(OBBT)index and layer-by-layer matching algorithm are proposed,which can effectively improve the search efficiency.In addition,in order to verify the correctness and integrity of the search results,the verification labels corresponding to the index keywords are stored in the leaf nodes of OBBT.Finally,the security analysis shows that the scheme is non-adaptive semantically secure,and the performance analysis shows that compared with the previous scheme search efficiency is improved obviously.2.Support wildcard and fuzzy search encryption scheme.The scheme uses features to capture keywords,and realizes both wildcard search and fuzzy keyword search by measuring the similarity of feature sets.In order to calculate the similarity between feature sets,the vector space model is used to construct keyword indexes and trapdoors,the inner product matching algorithm is used to calculate the relevance scores.The documents are ranked by the relevance scores and the matching documents are returned according to the search requirements.In addition,using the Bloom Filter optimization scheme reduces the index storage overhead and search time.Finally,security analysis shows that this scheme is non-adaptive semantic security,and performance analysis shows that the optimized scheme has good performance in terms of storage and search efficiency.