Fuzzy Keyword Set Research Articles

Fuzzy Keyword Searchable Encryption Scheme Based on Blockchain

Searchable encryption is a keyword-based ciphertext retrieval scheme, which can selectively retrieve encrypted documents on encrypted cloud data. Most existing searchable encryption schemes focus only on exact keyword searches and cannot return data of interest in fuzzy search. In addition, during the searchable encryption, the cloud server may return invalid results to the data user to save computing costs or for other reasons. At the same time, the user may refuse to pay the service fee after receiving the correct result. To solve the above problems, this paper proposes a fuzzy keyword searchable encryption scheme based on blockchain, which uses edit distance to generate fuzzy keyword sets and generates a secure index with verification tags for each fuzzy keyword set to verify the authenticity of the returned results. The penalty mechanism is introduced through the blockchain to realize the fairness of service payment between users and cloud servers. Security analysis shows that the scheme achieves non-adaptive semantic security. Performance analysis and functional comparison show that the scheme is effective and can meet the requirements of searching applications in the cloud environment.

An Intelligent Fuzzy Phrase Search Scheme Over Encrypted Network Data for IoT

With the popularization of various applications of the Internet of Things (IoT), a large number of smart devices are connected to the IoT to form an interconnected network. Because the amount of network data generated by IoT devices is huge, data owners prefer to outsource these data to the cloud for releasing them from the local storage burden. Meanwhile, in order to protect the privacy of the network data generated by IoT devices, data owners usually encrypt them before outsourcing them to the cloud. Phrase search encryption plays an important role in the IoT-based applications. To the best of our knowledge, all existing phrase search encryption schemes cannot work when user makes spelling errors. In addition, many existing phrase search encryption schemes build the secure index based on the relative position of keywords, which may lead to inaccurate search results. In order to address these problems, we propose an intelligent fuzzy phrase search scheme over encrypted network data for IoT. In this scheme, we construct a fuzzy keyword set for each distinct keyword, which can efficiently address the spelling mistakes. Moreover, we build the binary matrix for the document collection, which can quickly achieve multi-keyword search. In order to accurately determine whether the keywords in the query phrases are consecutive, we build the look-up table for each document. Experimental result shows that the proposed scheme achieves high efficiency and accuracy.

Constrained top-k nearest fuzzy keyword queries on encrypted graph in road network

With the gradual growth of road networks, the graphs used to represent road networks have been becoming larger and larger. It is a preferable choice for the user to outsource large-scale graphs for road networks to cloud and allow the cloud to store and query the information from graphs for him. It improves query efficiency greatly and reduces the user’s burden remarkably. To protect the privacy of graph data, the user has to encrypt the graph before uploading it to the cloud. It makes performing query on the encrypted graph become a challenge. In this paper, we propose the first scheme for performing a constrained top-k nearest keyword query on an encrypted graph, even if a typo is made by the user. In the proposed scheme, we construct a new index structure based on the 2-hop cover label index to calculate the constrained shortest distance. In order to support fuzzy keyword query, we generate the fuzzy keyword set to build the keyword index in the graph. The security analysis shows the proposed scheme satisfies CQA-security and the experiments demonstrate the proposed scheme is efficient.

Verifying Fuzzy Keyword Search Over Cipher Text in Cloud Computing

To enhance the potency of knowledge looking out, most knowledge house owners store their knowledge files in numerous cloud servers within the kind of ciphertext. Thus, economical search victimization fuzzy keywords become a vital issue in such a cloud computing atmosphere. Searchable cryptography will support knowledge user to select and retrieve the cipher documents over encrypted cloud knowledge by keyword-based search. Most of the prevailing searchable encryption schemes solely specialize in the precise keyword search. When knowledge user makes writing system errors, these schemes fail to come to the results of interest. In searchable encryption, the cloud server may come to the invalid result to knowledge user for saving the computation price or alternative reasons. Therefore, these precise keyword search schemes notice very little sensible significance in real-world applications. So as to deal with these problems, we tend to propose unique verifiable fuzzy keyword search theme over encrypted cloud knowledge. We tend to propose a verifiable precise keyword search theme which extend this theme to the fuzzy keyword search theme. Here we tend to thus propose a system for fuzzy keyword sets rather than precise word search. This will help us drastically to reduce the costs and it also allows to have multi-users using the system simultaneously.

An Efficient Approach for Secure Storage, Search using AES in Cloud Storage

The expanded rate of development and adaption of distributed computing, day by day, more delicate data is being brought together onto the cloud. For the security of profitable data, the information must be encoded before externalization. The current inquiry procedures enable the client to seek over encoded information utilizing keyword yet these methods represent just correct hunt. There is no resilience for grammatical errors and organization irregularities which are typical client conduct. This makes compelling information stockpiling and use an exceptionally difficult errand, providing client seeking extremely baffling and wasteful. In this paper, we concentrate on secure capacity utilizing Advanced Encryption Standard (AES) and data recovery by performing Fuzzysearch on information which is scrambled while transferring on the cloud. We are proposing the execution of a progressed Fuzzykeywordtechnique called the Wildcard based procedures which restores the coordinating records when clients seeking inputs definitely coordinate the predefined keyword or the nearest conceivable coordinating documents in light of likeness catchphrase semantics when correct match comes up short. In the proposed method, using alter separation to measure keywords similitude and build up a proficient strategies for developing fuzzy keyword sets, which concentrate on diminishing the capacity and portrayal overtop.

MinHash-Based Fuzzy Keyword Search of Encrypted Data across Multiple Cloud Servers

To enhance the efficiency of data searching, most data owners store their data files in different cloud servers in the form of cipher-text. Thus, efficient search using fuzzy keywords becomes a critical issue in such a cloud computing environment. This paper proposes a method that aims at improving the efficiency of cipher-text retrieval and lowering storage overhead for fuzzy keyword search. In contrast to traditional approaches, the proposed method can reduce the complexity of Min-Hash-based fuzzy keyword search by using Min-Hash fingerprints to avoid the need to construct the fuzzy keyword set. The method will utilize Jaccard similarity to rank the results of retrieval, thus reducing the amount of calculation for similarity and saving a lot of time and space overhead. The method will also take consideration of multiple user queries through re-encryption technology and update user permissions dynamically. Security analysis demonstrates that the method can provide better privacy preservation and experimental results show that efficiency of cipher-text using the proposed method can improve the retrieval time and lower storage overhead as well.

Fuzzy keyword search over encrypted data in cloud computing

As Cloud Computing becomes prevalent, more and more sensitive information are being centralized into the cloud. For the protection of data privacy, sensitive data usually have to be encrypted before outsourcing, which makes effective data utilization a very challenging task. Although traditional searchable encryption schemes allow a user to securely search over encrypted data through keywords and selectively retrieve files of interest, these techniques support only exact keyword search. This significant drawback makes existing techniques unsuitable in cloud computing as it is greatly affect system usability, rendering user searching experiences very frustrating and system efficiency very low. In this paper, for the first time we formalize and solve the problem of effective fuzzy keyword search over encrypted cloud while maintaining keyword privacy. In our solution, we exploit edit distance to quantify keyword similarity and develop new advanced technique on constructing fuzzy keyword sets which greatly reduces the storage and representation overheads. In this way, we show that our proposed solution is secure and privacy preserving, while realizing the goal of fuzzy keyword search.

Enabling Efficient Verifiable Fuzzy Keyword Search Over Encrypted Data in Cloud Computing

Searchable encryption can support data user to selectively retrieve the cipher documents over encrypted cloud data by keyword-based search. Most of the existing searchable encryption schemes only focus on the exact keyword search. When data user makes spelling errors, these schemes fail to return the result of interest. In searchable encryption, the cloud server might return the invalid result to data user for saving the computation cost or other reasons. Therefore, these exact keyword search schemes find little practical significance in real-world applications. In order to address these issues, we propose a novel verifiable fuzzy keyword search scheme over encrypted cloud data. For the purpose of introducing this scheme, we first propose a verifiable exact keyword search scheme and then extend this scheme to the fuzzy keyword search scheme. In the fuzzy keyword search scheme, we employ the linked list as our secure index to achieve the efficient storage. We construct a linked list with three nodes for each exact keyword and generate a fuzzy keyword set for it. To reduce the computation cost and the storage space, we generate one index vector for each fuzzy keyword set, rather than each fuzzy keyword. To resist malicious behaviors of the cloud server, we generate an authentication label for each fuzzy keyword to verify the authenticity of the returned ciphertexts. Through security analysis and experiment evaluation, we show that our proposed schemes are secure and efficient.

Revisiting Asymmetric Classifier Fuzzy Keyword Search with Performance Isolated Intertenant Storage Clusters in Public Cloud

Background/Objectives: Virtual Clusters enabled users across globe to be able to access virtual machines, transact and deploy applications. Intertenant cloud customers demand availability and performance isolation from the cloud. Methods/Statistical Analysis: Though fair allocation of resources guarantees performance isolation of intra-tenants in SaaS applications, it is still a challenging task in intertenant IaaS cloud. Findings: Existing Universal keyword classifier is revisited to suggest a new scheme named Refined Asymmetric Classifier Fuzzy Keyword Search. The Classifier Search server utilizes universal keyword classifier for the search keyword request to greatly reduce the searching time by learning the search path pattern for all the keywords in the Fuzzy keyword set. In addition to this, the cloud sevice providers of our proposed scheme utilizes Performance Isolated Intertenant Storage Cluster to provide availability and performance isolation. Our implementation outcome have shown that our proposed searching scheme minimizes searching time on the cloud storage server by utilizing the data effectively with high availability and predictable performance isolation. Applications/Improvements: This facilitates the cloud service provider to hold back the time to serve multiple customers as the searching time is absolutely diminished. Keywords: Asymmetric Encryption, Intertenancy, Keyword Classifier, Performance Isolation, Storage Clusters

Effective Data Utilization in Public Cloud through Hash Table Assorted Trie Indexed Encrypted Fuzzy Search

Cloud computing offers seamless service in the recent past to provide cloud infrastructure as a service that facilitates number of third party data owners across the world. Owing to various advantages like low infrastructure cost, high flexibility and ease of managing data, public cloud service has been widely adopted by several data owners. Cloud computing supports third party owners to optimize their cost spent towards cloud resources and infrastructure for their own data. While data owners are convinced with the security of individual data, the key is to make effective data utilization. This paper presents a novel approach hash table assorted trie encrypted fuzzy search method that creates wild card-based fuzzy keyword set to provide effective data utilization. It also creates hash table assorted trie fuzzy searchable index for fuzzy keyword set that resolves typos and representation inconsistencies and reduces searching time. The objective of the proposed searching method is to utilize the data effectively in terms of searching time, total number of files accessed from the untrusted cloud storage server.

Universal Keyword Classifier on Public Key Based Encrypted Multikeyword Fuzzy Search in Public Cloud.

Cloud computing has pioneered the emerging world by manifesting itself as a service through internet and facilitates third party infrastructure and applications. While customers have no visibility on how their data is stored on service provider's premises, it offers greater benefits in lowering infrastructure costs and delivering more flexibility and simplicity in managing private data. The opportunity to use cloud services on pay-per-use basis provides comfort for private data owners in managing costs and data. With the pervasive usage of internet, the focus has now shifted towards effective data utilization on the cloud without compromising security concerns. In the pursuit of increasing data utilization on public cloud storage, the key is to make effective data access through several fuzzy searching techniques. In this paper, we have discussed the existing fuzzy searching techniques and focused on reducing the searching time on the cloud storage server for effective data utilization. Our proposed Asymmetric Classifier Multikeyword Fuzzy Search method provides classifier search server that creates universal keyword classifier for the multiple keyword request which greatly reduces the searching time by learning the search path pattern for all the keywords in the fuzzy keyword set. The objective of using BTree fuzzy searchable index is to resolve typos and representation inconsistencies and also to facilitate effective data utilization.

Implementation of Fuzzy Keyword Search over Encrypted Data in Cloud Computing

With the increased rate of growth and adaptation of cloud computing, daily, more and more sensitive information is being centralized onto the cloud. For the protection of valuable proprietary information, the data must be encrypted before outsourcing. The existing search techniques allow the user to search over encrypted data using keywords but these techniques account for only exact keyword search. There is no tolerance for typos and format inconsistencies which are normal user behaviour. This makes effective data storage and utilization a very challenging task, rendering user searching very frustrating and inefficient. In this paper, we focus on secure storage using Advanced Encryption Standard (AES) and information retrieval by performing fuzzy keyword search on this encrypted data. We are proposing the implementation of an advanced fuzzy keyword search mechanism called the Wildcard Based technique which returns the matching files when users’ searching inputs exactly match the predefined keywords or the closest possible matching files based on similarity keyword semantics, when exact match fails. In the proposed solution, we exploit edit distance to quantify keywords similarity and develop an efficient technique for constructing fuzzy keyword sets, which focus on reducing the storage and representation overheads.