Internet of Things(IoT)interconnects devices via network protocols to enable intelligent sensing and control.Resource-constrained IoT devices rely on cloud servers for data storage and processing.However,this cloudass...Internet of Things(IoT)interconnects devices via network protocols to enable intelligent sensing and control.Resource-constrained IoT devices rely on cloud servers for data storage and processing.However,this cloudassisted architecture faces two critical challenges:the untrusted cloud services and the separation of data ownership from control.Although Attribute-based Searchable Encryption(ABSE)provides fine-grained access control and keyword search over encrypted data,existing schemes lack of error tolerance in exact multi-keyword matching.In this paper,we proposed an attribute-based multi-keyword fuzzy searchable encryption with forward ciphertext search(FCS-ABMSE)scheme that avoids computationally expensive bilinear pairing operations on the IoT device side.The scheme supportsmulti-keyword fuzzy search without requiring explicit keyword fields,thereby significantly enhancing error tolerance in search operations.It further incorporates forward-secure ciphertext search to mitigate trapdoor abuse,as well as offline encryption and verifiable outsourced decryption to minimize user-side computational costs.Formal security analysis proved that the FCS-ABMSE scheme meets both indistinguishability of ciphertext under the chosen keyword attacks(IND-CKA)and the indistinguishability of ciphertext under the chosen plaintext attacks(IND-CPA).In addition,we constructed an enhanced variant based on type-3 pairings.Results demonstrated that the proposed scheme outperforms existing ABSE approaches in terms of functionalities,computational cost,and communication cost.展开更多
To solve the problem of data recovery on free disk sectors, an approach of data recovering based on intelligent pattern matching is proposed in this paper. Different from the methods based on the file directory, this ...To solve the problem of data recovery on free disk sectors, an approach of data recovering based on intelligent pattern matching is proposed in this paper. Different from the methods based on the file directory, this approach utilizes the consistency among the data on the disk. A feature pattern library is established based on different types of fries according to the internal constructions of text. Data on sectors will be classified automatically by data clustering and evaluating. When the conflict happens on data classification, the digestion will be initiated by adopting context pattern. Based on this approach, the paper achieved the data recovery system aiming at pattern matching of txt, word and PDF fries. Raw and formatting recovery tests proved that the system works well.展开更多
This paper mainly studies case representation based on fuzzy technology, the comparing framework of case properties and the method of similarity assessment. Firstly, this paper proposes the method of case representati...This paper mainly studies case representation based on fuzzy technology, the comparing framework of case properties and the method of similarity assessment. Firstly, this paper proposes the method of case representation based on fuzzy technology. Secondly, it discusses the comparing framework of case fuzzy properties. Thirdly, it presents the case representation framework composed of structure data and related properties and b＇ased on which it studies the method and step of gaining case similarity assessment through adjusting similarity value of a property. This paper proposes a similarity assessment method in comparing stage of CBR using fuzzy technology. This method not only simples the computing complexity of CBR in comparing stage but also resolves the difficulties of similarity assessment on different levels.展开更多
This article introduces the developing process, the main idea and the method of FBEST (Fuzzy set theory Based Expert System Tool) reasoning mechanism.The method reasonably solves the problem of various inputting way...This article introduces the developing process, the main idea and the method of FBEST (Fuzzy set theory Based Expert System Tool) reasoning mechanism.The method reasonably solves the problem of various inputting ways and proposition reasoning which possesses both fuzziness and randomness in ES.展开更多
文摘Internet of Things(IoT)interconnects devices via network protocols to enable intelligent sensing and control.Resource-constrained IoT devices rely on cloud servers for data storage and processing.However,this cloudassisted architecture faces two critical challenges:the untrusted cloud services and the separation of data ownership from control.Although Attribute-based Searchable Encryption(ABSE)provides fine-grained access control and keyword search over encrypted data,existing schemes lack of error tolerance in exact multi-keyword matching.In this paper,we proposed an attribute-based multi-keyword fuzzy searchable encryption with forward ciphertext search(FCS-ABMSE)scheme that avoids computationally expensive bilinear pairing operations on the IoT device side.The scheme supportsmulti-keyword fuzzy search without requiring explicit keyword fields,thereby significantly enhancing error tolerance in search operations.It further incorporates forward-secure ciphertext search to mitigate trapdoor abuse,as well as offline encryption and verifiable outsourced decryption to minimize user-side computational costs.Formal security analysis proved that the FCS-ABMSE scheme meets both indistinguishability of ciphertext under the chosen keyword attacks(IND-CKA)and the indistinguishability of ciphertext under the chosen plaintext attacks(IND-CPA).In addition,we constructed an enhanced variant based on type-3 pairings.Results demonstrated that the proposed scheme outperforms existing ABSE approaches in terms of functionalities,computational cost,and communication cost.
文摘To solve the problem of data recovery on free disk sectors, an approach of data recovering based on intelligent pattern matching is proposed in this paper. Different from the methods based on the file directory, this approach utilizes the consistency among the data on the disk. A feature pattern library is established based on different types of fries according to the internal constructions of text. Data on sectors will be classified automatically by data clustering and evaluating. When the conflict happens on data classification, the digestion will be initiated by adopting context pattern. Based on this approach, the paper achieved the data recovery system aiming at pattern matching of txt, word and PDF fries. Raw and formatting recovery tests proved that the system works well.
文摘This paper mainly studies case representation based on fuzzy technology, the comparing framework of case properties and the method of similarity assessment. Firstly, this paper proposes the method of case representation based on fuzzy technology. Secondly, it discusses the comparing framework of case fuzzy properties. Thirdly, it presents the case representation framework composed of structure data and related properties and b＇ased on which it studies the method and step of gaining case similarity assessment through adjusting similarity value of a property. This paper proposes a similarity assessment method in comparing stage of CBR using fuzzy technology. This method not only simples the computing complexity of CBR in comparing stage but also resolves the difficulties of similarity assessment on different levels.
文摘This article introduces the developing process, the main idea and the method of FBEST (Fuzzy set theory Based Expert System Tool) reasoning mechanism.The method reasonably solves the problem of various inputting ways and proposition reasoning which possesses both fuzziness and randomness in ES.
