With the continuous growth of exponential data in IoT,it is usually chosen to outsource data to the cloud server.However,cloud servers are usually provided by third parties,and there is a risk of privacy leakage.Encry...With the continuous growth of exponential data in IoT,it is usually chosen to outsource data to the cloud server.However,cloud servers are usually provided by third parties,and there is a risk of privacy leakage.Encrypting data can ensure its security,but at the same time,it loses the retrieval function of IoT data.Searchable Encryption(SE)can achieve direct retrieval based on ciphertext data.The traditional searchable encryption scheme has the problems of imperfect function,low retrieval efficiency,inaccurate retrieval results,and centralized cloud servers being vulnerable and untrustworthy.This paper proposes an Efficient searchable encryption scheme supporting fuzzy multi-keyword ranking search on the blockchain.The blockchain and IPFS are used to store the index and encrypted files in a distributed manner respectively.The tamper resistance of the distributed ledger ensures the authenticity of the data.The data retrieval work is performed by the smart contract to ensure the reliability of the data retrieval.The Local Sensitive Hash(LSH)function is combined with the Bloom Filter(BF)to realize the fuzzy multi-keyword retrieval function.In addition,to measure the correlation between keywords and files,a new weighted statistical algorithm combining RegionalWeight Score(RWS)and Term Frequency–Inverse Document Frequency(TF-IDF)is proposed to rank the search results.The balanced binary tree is introduced to establish the index structure,and the index binary tree traversal strategy suitable for this scheme is constructed to optimize the index structure and improve the retrieval efficiency.The experimental results show that the scheme is safe and effective in practical applications.展开更多
In a cloud environment,outsourced graph data is widely used in companies,enterprises,medical institutions,and so on.Data owners and users can save costs and improve efficiency by storing large amounts of graph data on...In a cloud environment,outsourced graph data is widely used in companies,enterprises,medical institutions,and so on.Data owners and users can save costs and improve efficiency by storing large amounts of graph data on cloud servers.Servers on cloud platforms usually have some subjective or objective attacks,which make the outsourced graph data in an insecure state.The issue of privacy data protection has become an important obstacle to data sharing and usage.How to query outsourcing graph data safely and effectively has become the focus of research.Adjacency query is a basic and frequently used operation in graph,and it will effectively promote the query range and query ability if multi-keyword fuzzy search can be supported at the same time.This work proposes to protect the privacy information of outsourcing graph data by encryption,mainly studies the problem of multi-keyword fuzzy adjacency query,and puts forward a solution.In our scheme,we use the Bloom filter and encryption mechanism to build a secure index and query token,and adjacency queries are implemented through indexes and query tokens on the cloud server.Our proposed scheme is proved by formal analysis,and the performance and effectiveness of the scheme are illustrated by experimental analysis.The research results of this work will provide solid theoretical and technical support for the further popularization and application of encrypted graph data processing technology.展开更多
In this paper, we focus on the fuzzy keyword search problem over the encrypted cloud data in the cloud computing and propose a novel Two-Step-Bloom-Secure-Filter （TSBSF） scheme based on Bloom filter to realize the e...In this paper, we focus on the fuzzy keyword search problem over the encrypted cloud data in the cloud computing and propose a novel Two-Step-Bloom-Secure-Filter （TSBSF） scheme based on Bloom filter to realize the efficiency and flexibility of data use. The proposed scheme not only reduces the space complexity significantly but also supports the data update with low time complexity and guarantees the search accuracy. Experimental results on real world data have certified the validity and practicality of this novel method.展开更多
With the ever-increasing number of natural disasters warning documents in document databases, the document database is becoming an economic and efficient way for enterprise staffs to learn and understand the contents ...With the ever-increasing number of natural disasters warning documents in document databases, the document database is becoming an economic and efficient way for enterprise staffs to learn and understand the contents of the natural disasters warning through searching for necessary text documents. Generally, the document database can recommend a mass of documents to the enterprise staffs through analyzing the enterprise staff's precisely typed keywords. In fact, these recommended documents place a heavy burden on the enterprise staffs to learn and select as the enterprise staffs have little background knowledge about the contents of the natural disasters warning. Thus, the enterprise staffs fail to retrieve and select appropriate documents to achieve their desired goals.Considering the above drawbacks, in this paper, we propose a fuzzy keywords-driven Natural Disasters Warning Documents retrieval approach(named NDWDkeyword). Through the text description mining of documents and the fuzzy keywords searching technology, the retrieval approach can precisely capture the enterprise staffs' target requirements and then return necessary documents to the enterprise staffs. Finally, a case study is run to explain our retrieval approach step by step and demonstrate the effectiveness and feasibility of our proposal.展开更多
Searchable encryption is an effective way to ensure the security and availability of encrypted outsourced cloud data.Among existing solutions,the keyword exact search solution is relatively inflexible,while the fuzzy ...Searchable encryption is an effective way to ensure the security and availability of encrypted outsourced cloud data.Among existing solutions,the keyword exact search solution is relatively inflexible,while the fuzzy keyword search solution either has a high index overhead or suffers from the falsepositive.Furthermore,no existing fuzzy keyword search solution considers the homoglyph search on encrypted data.In this paper,we propose an efficient privacy-preserving homoglyph search scheme supporting arbitrary languages(POSA,in short).We enhance the performance of the fuzzy keyword search in three aspects.Firstly,we formulate the similarity of homoglyph and propose a privacy-preserving homoglyph search.Secondly,we put forward an index build mechanism without the false-positive,which reduces the storage overhead of the index and is suitable for arbitrary languages.Thirdly,POSA returns just the user’s search,i.e.,all returned documents contain the search keyword or its homoglyph.The theoretical analysis and experimental evaluations on real-world datasets demonstrate the effectiveness and efficiency of POSA.展开更多
Improvements in fuel consumption and emissions of hybrid electric vehicle(HEV)heavily depend upon an efficient energy management strategy(EMS).This paper presents an optimizing fuzzy control strategy of parallel hybri...Improvements in fuel consumption and emissions of hybrid electric vehicle(HEV)heavily depend upon an efficient energy management strategy(EMS).This paper presents an optimizing fuzzy control strategy of parallel hybrid electric vehicle em-展开更多
基金funded by the Jilin Provincial Department of Education Scientific Research Project(Project No.JJKH20250872KJ).
文摘With the continuous growth of exponential data in IoT,it is usually chosen to outsource data to the cloud server.However,cloud servers are usually provided by third parties,and there is a risk of privacy leakage.Encrypting data can ensure its security,but at the same time,it loses the retrieval function of IoT data.Searchable Encryption(SE)can achieve direct retrieval based on ciphertext data.The traditional searchable encryption scheme has the problems of imperfect function,low retrieval efficiency,inaccurate retrieval results,and centralized cloud servers being vulnerable and untrustworthy.This paper proposes an Efficient searchable encryption scheme supporting fuzzy multi-keyword ranking search on the blockchain.The blockchain and IPFS are used to store the index and encrypted files in a distributed manner respectively.The tamper resistance of the distributed ledger ensures the authenticity of the data.The data retrieval work is performed by the smart contract to ensure the reliability of the data retrieval.The Local Sensitive Hash(LSH)function is combined with the Bloom Filter(BF)to realize the fuzzy multi-keyword retrieval function.In addition,to measure the correlation between keywords and files,a new weighted statistical algorithm combining RegionalWeight Score(RWS)and Term Frequency–Inverse Document Frequency(TF-IDF)is proposed to rank the search results.The balanced binary tree is introduced to establish the index structure,and the index binary tree traversal strategy suitable for this scheme is constructed to optimize the index structure and improve the retrieval efficiency.The experimental results show that the scheme is safe and effective in practical applications.
基金This research was supported in part by the Nature Science Foundation of China(Nos.62262033,61962029,61762055,62062045 and 62362042)the Jiangxi Provincial Natural Science Foundation of China(Nos.20224BAB202012,20202ACBL202005 and 20202BAB212006)+3 种基金the Science and Technology Research Project of Jiangxi Education Department(Nos.GJJ211815,GJJ2201914 and GJJ201832)the Hubei Natural Science Foundation Innovation and Development Joint Fund Project(No.2022CFD101)Xiangyang High-Tech Key Science and Technology Plan Project(No.2022ABH006848)Hubei Superior and Distinctive Discipline Group of“New Energy Vehicle and Smart Transportation”,the Project of Zhejiang Institute of Mechanical&Electrical Engineering,and the Jiangxi Provincial Social Science Foundation of China(No.23GL52D).
文摘In a cloud environment,outsourced graph data is widely used in companies,enterprises,medical institutions,and so on.Data owners and users can save costs and improve efficiency by storing large amounts of graph data on cloud servers.Servers on cloud platforms usually have some subjective or objective attacks,which make the outsourced graph data in an insecure state.The issue of privacy data protection has become an important obstacle to data sharing and usage.How to query outsourcing graph data safely and effectively has become the focus of research.Adjacency query is a basic and frequently used operation in graph,and it will effectively promote the query range and query ability if multi-keyword fuzzy search can be supported at the same time.This work proposes to protect the privacy information of outsourcing graph data by encryption,mainly studies the problem of multi-keyword fuzzy adjacency query,and puts forward a solution.In our scheme,we use the Bloom filter and encryption mechanism to build a secure index and query token,and adjacency queries are implemented through indexes and query tokens on the cloud server.Our proposed scheme is proved by formal analysis,and the performance and effectiveness of the scheme are illustrated by experimental analysis.The research results of this work will provide solid theoretical and technical support for the further popularization and application of encrypted graph data processing technology.
基金Supported by the National Natural Science Foundation of China (61170234) (60803155)the Strategic Priority Research Program of the Chinese Academy of Sciences (XDA06030601)the Funding of Science and Technology on Information Assurance Laboratory (KJ-13-02)
文摘In this paper, we focus on the fuzzy keyword search problem over the encrypted cloud data in the cloud computing and propose a novel Two-Step-Bloom-Secure-Filter （TSBSF） scheme based on Bloom filter to realize the efficiency and flexibility of data use. The proposed scheme not only reduces the space complexity significantly but also supports the data update with low time complexity and guarantees the search accuracy. Experimental results on real world data have certified the validity and practicality of this novel method.
文摘With the ever-increasing number of natural disasters warning documents in document databases, the document database is becoming an economic and efficient way for enterprise staffs to learn and understand the contents of the natural disasters warning through searching for necessary text documents. Generally, the document database can recommend a mass of documents to the enterprise staffs through analyzing the enterprise staff's precisely typed keywords. In fact, these recommended documents place a heavy burden on the enterprise staffs to learn and select as the enterprise staffs have little background knowledge about the contents of the natural disasters warning. Thus, the enterprise staffs fail to retrieve and select appropriate documents to achieve their desired goals.Considering the above drawbacks, in this paper, we propose a fuzzy keywords-driven Natural Disasters Warning Documents retrieval approach(named NDWDkeyword). Through the text description mining of documents and the fuzzy keywords searching technology, the retrieval approach can precisely capture the enterprise staffs' target requirements and then return necessary documents to the enterprise staffs. Finally, a case study is run to explain our retrieval approach step by step and demonstrate the effectiveness and feasibility of our proposal.
基金This work was supported in part by the National Natural Science Foundation of China(Grant Nos.U1804263 and 61702105).
文摘Searchable encryption is an effective way to ensure the security and availability of encrypted outsourced cloud data.Among existing solutions,the keyword exact search solution is relatively inflexible,while the fuzzy keyword search solution either has a high index overhead or suffers from the falsepositive.Furthermore,no existing fuzzy keyword search solution considers the homoglyph search on encrypted data.In this paper,we propose an efficient privacy-preserving homoglyph search scheme supporting arbitrary languages(POSA,in short).We enhance the performance of the fuzzy keyword search in three aspects.Firstly,we formulate the similarity of homoglyph and propose a privacy-preserving homoglyph search.Secondly,we put forward an index build mechanism without the false-positive,which reduces the storage overhead of the index and is suitable for arbitrary languages.Thirdly,POSA returns just the user’s search,i.e.,all returned documents contain the search keyword or its homoglyph.The theoretical analysis and experimental evaluations on real-world datasets demonstrate the effectiveness and efficiency of POSA.
基金supported by the Natural Science Foundation of Hubei Province(Grant No.2015CFB586)
文摘Improvements in fuel consumption and emissions of hybrid electric vehicle(HEV)heavily depend upon an efficient energy management strategy(EMS).This paper presents an optimizing fuzzy control strategy of parallel hybrid electric vehicle em-
