Top PDF An Efficient File Retrieval from Cloud Servers Using Multi Keyword Sets

An Efficient File Retrieval from Cloud Servers Using Multi Keyword Sets

An Efficient File Retrieval from Cloud Servers Using Multi Keyword Sets

The existing techniques for keyword-based information retrieval, which are wide, used on the plaintext data to the search from the cloud server. A traditional way to reduce information seepage is data encryption. However, this will make server-side data operation, such as penetrating on encrypted data, become a very challenging task. In the recent years, researchers have proposed many symbols text search scheme by incorporate the cryptography technique. These methods have been proven with provable security, but their methods need massive operations and have high time complexity. In this system have a lot of security issues are there Keyword Guessing Attack will happen the hackers can easily guess the keyword then they can easily hack our content from the cloud server. Existing search system will provide the result only based on the Boolean keyword matching system, it means whether it will find the exact file name same as the keyword than the file will be retrieved from the server, it won’t provide any search result for misspelled keywords. And also the existing search system never provide the result based on similar keyword
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ENHANCED SEARCH SCHEME BASED ON EFFICIENT MULTI-KEYWORD RANKED SEARCH IN CLOUD

ENHANCED SEARCH SCHEME BASED ON EFFICIENT MULTI-KEYWORD RANKED SEARCH IN CLOUD

As the popularity of cloud increases, a large number of data owners were motivated for outsourcing the information to the cloud servers which will be convenient for users and also reduction in cost for managing the data. But confidential information has to be encrypted in prior to outsource the data to provide privacy and security that can be used for data retrieval through keyword based scheme. The paper provides a multiple keyword rank search technique on data encrypted that can be used to support dynamic operations such as insertion and deletion of data in document. Widely used models are vector space and TF-IDF were commonly used in combination with the query generation and construction of index. An index structure is constructed on the basis of tree and an algorithm is proposed which is depth-first search tree, a greedy algorithm that helps to provide efficiency in multiple keyword rank search. A secure algorithm called KNN is used for encrypting the query vectors and also the index. The usage of KNN algorithm also provides accurate score computation among the query vectors and indexes which are encrypted. To protect from statistical attacks, apparition words were included in the index to bind with the search result. As a special tree-based indexing structure was implemented, the proposed method will achieve more efficiency in time for search and also provides flexibility for performing insertion and deletion operations in a document. Substantial procedures were used for the demonstration of the proposed scheme for achieving greater efficiency.
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Secure and Efficient Multi-keyword Ranked Search Method on Cloud

Secure and Efficient Multi-keyword Ranked Search Method on Cloud

The extensive use of cloud services has resulted in dramatic growth in volume of data which has made information retrieval much more difficult than before. Even text documents are encrypted before being outsourced to cloud servers. This helps to protect user’s data privacy. Existing techniques to search over encrypted data are not suitable for a huge data environment. Due to the blind encryption, relationship between the documents is concealed which further leads to search accuracy performance degradation. Therefore it is necessary to adopt an approach to support more search semantic and for fast search within enormous data. A hierarchical clustering method for cipher text search is proposed in this paper. The proposed approach clusters the documents based on the minimum similarity threshold, and then partitions the resultant clusters into sub-clusters until the constraint on the maximum size of cluster is reached. The very first thing which cloud server does is that it performs search activity and then selects the k documents (previously decided by the user and sent to the cloud server) from the minimum desired sub-category. To request desired documents, instead of using single keyword search query, multi-keyword search technique is proposed.
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An Economical multi - keyword seek for
conserving energy over Mobile Cloud: TEES
 

      P. Sreevenkatramana,   Dr.AR.Arunachalam  Abstract PDF  IJIRMET1602040041

An Economical multi - keyword seek for conserving energy over Mobile Cloud: TEES P. Sreevenkatramana, Dr.AR.Arunachalam Abstract PDF IJIRMET1602040041

In the paper [3] Wang defined and solved the problem of secure ranked keyword search over encrypted cloud data. Ranked search greatly enhances system usability by enabling search result relevance ranking instead of sending undifferentiated results, and further ensures the file retrieval accuracy. Specifically, we explore the statistical measure approach. In the paper [4] proposed by Cong Wang, proposed a definition for ranked searchable symmetric encryption, and give an efficient design by properly utilizing the existing cryptographic primitive, order-preserving symmetric encryption (OPSE). Thorough analysis shows that the proposed solution enjoys “as-strong-as possible” security guarantee compared to previous SSE schemes, while correctly realizing the goal of ranked keyword search.In the paper [5], Shucheng Yu proposed a novel multi keyword fuzzy search scheme by exploiting the locality-sensitive hashing technique. Proposed scheme achieves fuzzy matching through algorithmic design rather than expanding the index file. It also eliminates the need of a predefined dictionary and effectively supports multiple keyword fuzzy searches without increasing the index or search complexity. Extensive analysis and experiments on real-world data show that the proposed scheme is secure, efficient and accurate. In the paper [6], Juan Ramos examined the results of applying Term Frequency Inverse Document Frequency (TF-IDF) to determine what words in a corpus of documents might be more favorable to use in a query. As the term implies, TF-IDF calculates the values for each word in a document through an inverse proportion of the frequency of the word in a particular document to the percentage of documents the word appears in. Words with high TF-IDF numbers imply a strong relationship with the document they appear in,suggesting that if that word were to appear in a query, the document could be of interest to the user.
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Secure Multi keyword Retrieval over Encrypted          Cloud Data

Secure Multi keyword Retrieval over Encrypted Cloud Data

In cloud computing, data owner may share their outsourced data with a number of users, who might want to only retrieve the data files they are fascinated with. One most popular way is do probing by utilizing keyword base retrieval. Keyword search is data retrieval accommodation which applied on plain text scenarios, in which user retrieve pertinent files from the sets of file predicated on keywords. But this scenario is becomes arduous task when it consider in the case of cipher text, because we can do only circumscribed operations on encrypted data. To ameliorate feasibility and preserve on the expense in the cloud paradigm, it is preferred to get the retrieval result with the most pertinent files that match users interest in lieu of all the files, which denotes that the files should be ranked in the order of pertinence by users interest and only the files with the highest pertinence are sent back to users. Searchable symmetric encryption schemes is enable search on cipher text but it support only Boolean keyword search, without considering the difference of pertinence with the queried keyword of these files in the result. Searchable symmetric encryption schemes are suffer from two problems-Boolean representations and how to strike a balance between security and efficiency. The concepts of similarity relevance and scheme robustness to formulate the privacy issue in searchable encryption schemes and to solve in security problem by using two round searchable encryption scheme.
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Improved Privacy Multi-Keyword Based Secure Retrieval Scheme For Cloud Data

Improved Privacy Multi-Keyword Based Secure Retrieval Scheme For Cloud Data

IPMKRS is an attempt to improve the security of the cloud data by deriving the benefits of co-ordinate mating that aids in realizing the key features of the data documents based on search query. Specifically, inner product similarity is used for estimating the similarity of the data documents. The search potential for securing the cloud data is opti- mized. IPMKRS includes three steps - Cloud set-up, initiali- zation and retrieval. IPMKRS is mainly propounded for facil- itating the encryption of the cloud data using the concept of Multi-Keyword based Ranking (MKR). MKR is based on the technique of co-ordinate matching and the cloud servers are responsible for ranking the files that are stored on the server. This technique of ranking reduces the cost of com- munication that is incurred during the identification of top secure files on the file server. It also uses searchable key encryption for determining the optimally secure file on the server.
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Secure Fuzzy Multi-Keyword Ranked Search over Encrypted Cloud Data

Secure Fuzzy Multi-Keyword Ranked Search over Encrypted Cloud Data

cloud servers cannot be completely trusted to protect data, the files must be encrypted before outsourcing. The cloud server will provide keyword retrieval service to authorized users. There is a predefined set of keywords W and a new fuzzy keyword set F is built based on W. The data owner builds a searchable index I from F and then outsources the encrypted index and the encrypted files onto the cloud server. The computing power on user side is limited i.e. the operation on user side should be simplified .The data user at first generates a query and the keywords are kept concealed for privacy reasons. To search the document collection for the given keywords, an authorized user acquires a corresponding trapdoor T through search control mechanisms. Corresponding set of encrypted documents is returned upon receiving T from data user after searching index I. By ranking the search result according to coordinate matching, the document retrieval accuracy can be improved. An optional number k can be send along with the trapdoor T by the user to reduce the communication cost, as it sends back only top-k documents that are most relevant to the query. The data user can use the files after decrypting it.
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Searching Encrypted Data in Cloud Using Multi-Keyword Ranked       Search

Searching Encrypted Data in Cloud Using Multi-Keyword Ranked Search

cloud computing, more and more data owners are motivated to outsource their data to cloud servers for great convenience and reduced cost in data management. However, sensitive data should be encrypted before outsourcing for privacy requirements, which obsoletes data utilization like keyword-based document retrieval. In this paper, we present a secure multi-keyword ranked search scheme over encrypted cloud data, which simultaneously supports dynamic update operations like deletion and insertion of documents. Specifically, the vector space model and the widely-used TF_IDF model are combined in the index construction and query generation. We construct a special tree-based index structure and propose a “Greedy Depth-first Search” algorithm to provide efficient multi-keyword ranked search. The secure KNN algorithm is utilized to encrypt the index and query vectors, and meanwhile ensure accurate relevance score
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Multi Keyword Retrieval 
                          on Secured Cloud

Multi Keyword Retrieval on Secured Cloud

Abstract- An efficient method of cryptography with multiple keyword searches is proposed in this paper. This paper aims to provide searching a file over cloud environment using multiple keywords representing the file with various probable situations. The aim is to provide the security to its maximum extent by including encryption and decryption methods. Authorization of the users directly by the administrators allows the files involved to transfer more securely. Encryption and decryption of both file name and file which uses asymmetric and symmetric key algorithms respectively. The secret key is generated for each user to prevent any other user to misuse the file. The implementation of the project in the simple manner provides an easy to understand environment for the user. By using server side process to hold the most processes, the user can reduce the systems inefficiency. Client side system uses less work corresponding to the task needed to perform the basic role like ranking and arranging the files in the requested order. The solution can be applied to various applications because of is simplicity.
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File Security with Multi-Server File Distribution on Cloud

File Security with Multi-Server File Distribution on Cloud

Plutus is a cryptographic accumulator arrangement that enables defended book administration afterwards agreement abundant assurance on the book servers. In particular, it makes atypical use of cryptographic primitives to assure and allotment files. Plutus appearance awful scalable key administration while acceptance abandoned users to absorb absolute ascendancy over who gets admission to their files. We explain the mechanisms in Plutus to abate the amount of cryptographic keys exchanged amid users by appliance book groups, analyze book apprehend and address access, handle user abolishment efficiently, and acquiesce an untrusted server to accredit book writes. We accept congenital a ancestor of Plutus on OpenAFS. Measurements of this ancestor appearance that Plutus achieves able aegis with aerial commensurable to systems that encrypt all arrangement traffic.
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Data Integrity And Data Uploading In Cloud With Identity Based Proxy Oriented Encryption

Data Integrity And Data Uploading In Cloud With Identity Based Proxy Oriented Encryption

adding or updating the contents in the stored file instead of storing the entire file again. This is an efficient way to store the data in cloud with ease of work, minimizes the cost consumption and time consumption. The main aim of this model is to reduce the space in server. Also these services are extended to have a copy of resource by means of the multiple replica provable data possession (MRPDP) model. This model is used to ensure the resource maintenance by having a copy of resources in server and when one file is damaged, another file can retrieve the contents of the file. The auditing services are important to ensure whether the data owner is storing the useful resources in the cloud server or not. This is maintained by mean of the third-party auditor (TPA). This third-party auditor will ensure this services. Also multiple auditing tasks can be done at the same time in public cloud services, as they have many users. They extend the efficiency and security of public cloud services. Also they work dynamically in order to maintain the system dynamically, as there are many updates are carried out at a time in public cloud services. III. PROPOSED SYSTEM
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Title: CONFIDENTIALITY RETENTION IN KEYWORD-LIST RANKED SEARCH FOR ENCRYPTED CLOUD DATA

Title: CONFIDENTIALITY RETENTION IN KEYWORD-LIST RANKED SEARCH FOR ENCRYPTED CLOUD DATA

and beyond, sensitive data, for example, e-mails, personal health records, photo albums, tax documents, financial transactions, and so on, may have to be encrypted by data owners before outsourcing to the commercial public cloud this, however, obsoletes the traditional data utilization service based on plaintext keyword search. The trivial solution of downloading all the data and decrypting locally is clearly impractical, due to the huge amount of bandwidth cost in cloud scale systems. Thus, exploring privacy preserving and effective search service over encrypted cloud data is of paramount importance. Considering the potentially large number of on-demand data users and huge amount of outsourced data documents in the cloud, this problem is particularly challenging as it is extremely difficult to meet also the requirements of performance, system usability, and scalability. Cloud computing, a relatively new technology, has been gaining immense popularity over the last few years where user can rent software, hardware, infrastructure and computational recourse as per user basis. The cloud has three service models. In the Software as a Service (SaaS) model, the software or the applications are hosted over the cloud. These services are available to the customers based on the pay-as-per-use model. Google Apps and SALESFORCE are examples of this model. The Platform as a Service (PaaS) model provides a hosting environment for the client’s application. Examples for PaaS model are Google App Engine and Amazon Web Services. The Infrastructure as a Service (IaaS) model lets the client to dynamically scale up or scale down the resources like processing power, storage capacity, network bandwidth etc. Example: Amazon EC2, Eucalyptus, etc.
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ABSTRACT- Sensitive cloud data have to be encrypted to protect information safety measures, before outsourcing.

ABSTRACT- Sensitive cloud data have to be encrypted to protect information safety measures, before outsourcing.

Traditional searchable encryption has been widely studied as a cryptographic primitive, with a focus on security definition formalizations and efficiency improvements. Song et al. first introduced the notion of searchable encryption. They proposed a scheme in the symmetric key setting, where each word in the file is encrypted independently under a special two-layered encryption construction. Thus, a searching overhead is linear to the whole file collection length. Goh developed a Bloom filter-based per-file index, reducing the workload for each search request proportional to the number of files in the collection. Chang and Mitzenmacher also developed a similar per-file index scheme. To further enhance search efficiency, Curtmola et al. proposed a per-keyword-based approach, where a single encrypted hash table index is built for the entire file collection, with each entry consisting of the trapdoor of a keyword and an encrypted set of related file identifiers. Searchable encryption has also been considered in the public-key setting. Aiming at tolerance of both minor typos and format inconsistencies in the user search input, fuzzy keyword search over encrypted cloud data has been proposed by Li et al. in [9]. Very recently, a privacy-assured similarity search mechanism over outsourced cloud data has been explored by Wang et al. in [2]. Note that all these schemes support only Boolean keyword search and none of them support the ranked search problem which we are focusing on in this paper. Following our research on secure ranked search over encrypted data, very recently, Cao et al. [1] propose a privacy-preserving multi keyword ranked search scheme, which extends our previous work in [1] with support of multi keyword query. They choose the principle of “coordinate matching,” i.e., as many matches as possible, to capture the similarity between a multi keyword search query and data documents and later quantitatively formalize the principle by a secure inner product computation mechanism. One disadvantage of the scheme is that cloud server has to linearly traverse the whole index of all the documents for each search request, while ours is as efficient as existing SSE schemes with only constant search cost on cloud server.
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Secured file storage and retrieval in cloud using cryptography with secret key

Secured file storage and retrieval in cloud using cryptography with secret key

CRYPTOGRAPHY WITH SECRET KEY An approach to secure file storage and retrieval in cloud using cryptography has been proposed. The proposed method called “Secured file storage and retrieval in cloud using cryptography with secret key” an encryption technique is used to secure file in cloud and also secret key is used to enhance the security. In the existing system, encryption techniques alone used for file security but the proposed model uses secret key as a extra security feature while retrieving file from cloud. The proposed method consists of 5 phases. They are Register user details, User login, Secret key generation, File Encryption and Upload, File decryption and download. The system level design of the proposed model is given in the Fig 1(a),Fig 1(b).
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Efficient Image Retrieval Using Cloud Repository

Efficient Image Retrieval Using Cloud Repository

The author A. Karpathy and L. Fei-Fei proposed a model generating the descriptions of natural language of images and their regions. This approach have advantage of image data sets and their sentence descriptions to know the intermodal correspondences between language and visual data.The alignment model is based on combination of convolutional neural networks on image regions, bidirectional recurrent neural networks on sentences . The structured goal aligns two modalities through a multimodal model [9].

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SSS - EC: Secure Storage Services and Erasure Code Implementation in Cloud Computing

SSS - EC: Secure Storage Services and Erasure Code Implementation in Cloud Computing

Abstract-Cloud computing is sharing of resources on a larger scale which is cost effective and location independent. The level of security is low in cloud server for data safety. If at all security exists, the third party auditor should be allowed to access the entire data packets. In this paper a new cloud computing technique SSS-EC is proposed in which a Cloud server splits into different chunks and then encrypted. And the encrypted cloud server is kept in a replica cloud server as a backup. This encrypted data are converted into bytes and added parity bit process by the data owner in order to restrict TPA by accessing the original data.
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An Efficient Retrieval of Cloud Data using ECIES Scheme

An Efficient Retrieval of Cloud Data using ECIES Scheme

Clouds can be explained as pools of virtualized resources that can be easily used and accessed. For optimum resource utilization the resources in cloud can be reconfigured dynamically. With the help of strong cloud architectures its mass computing and storage centers organizations and individuals are benefited while utilizing them. Cloud computing basically contains virtualization, on-demand deployment, Internet delivery of services, open source software etc. [1]. With the help of internet and central remote servers cloud computing maintains data and applications. Cloud computing helps the consumers and businesses to use clouds applications and resources without installing and accessing the personal files on any computer through internet. Cloud Computing provides efficient computing by centralizing storage, memory, processing and bandwidth promising lower costs, rapid scaling, easier maintenance, service availability. The main focus needs upon the data security and privacy. Services provided by cloud computing are [2].
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A Survey on Secure and Aggressive Multi-Keyword Ranked Search Over Encrypted Cloud Data

A Survey on Secure and Aggressive Multi-Keyword Ranked Search Over Encrypted Cloud Data

Cong Wang, Ning Cao, KuiRen, Wenjing Lou, fellow, IEEE [3] in this paper they work on the ranked keyword search over encrypted data to reach economies of scale for Cloud Computing. They start from the study of existing searchable symmetric encryption (SSE) schemes and provide the definitions and framework for their proposed ranked searchable symmetric encryption (RSSE). Note that by following the same security bond of existing SSE, it would be very unsuitableto support ranked search functionality over encrypted data, as demonstrated in our basic scheme. The conversion of its demerits will show the proposed scheme. Searchable encryption allows data owner to outsource his data in an encrypted manner while maintaining the selectively-search ability over the encrypted data. Generally, searchable encryption can be achieved in its full functionality using an insensible RAMs. They first start with aeasy ideal scheme, where the security of their ranked searchable encryption is the same as previous SSE schemes, i.e., the user gets the ranked results without allow cloud server learn any additional information more than the access pattern and search pattern. However, this is achieved with the trade-off of efficiency: namely, either should the user wait for two round-trip time for each search request, or he may even lose the capability to perform top-k retrieval, resulting the unnecessary communication overhead. They believe the analysis of these demerits will lead to their main result. EFFICIENT RANKED SEARCHABLE SYMMETRICENCRYPTION SCHEME proposesthat causes the inefficiency of ranked searchable encryption. That is how to allow server quickly perform the ranking without actually knowing the relevance scores. Note that by resorting to OPSE, our security guarantee of RSSE is inherently weakened compared to SSE, as they now let server know the relevance order. However, this is the information they want to trade off for efficient RSSE, then they show how we can adapt it to suit our purpose for ranked searchable encryption with an “as- strong-as-possible” security warranty. Using Order Preserving Symmetric Encryption [OPSE]deterministic encryption scheme where the numerical ordering of the plaintexts gets preserved by the encryption function.
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Energy Efficient and Secured Cloud Data Handling with Multi-User Access Control Strategies

Energy Efficient and Secured Cloud Data Handling with Multi-User Access Control Strategies

Furthermore, the rigious proof had been represented to prove the security of their scheme. Popa et al. focused on web applications and proposed a new platform Mylar which is a combination of system techniques and novel cryptographic primitives, including data sharing, computing over encrypted data and verifying application code. The results with 6 applications showed that Mylar is a good multi-user web application with data sharing. In earlier system, the authors proposed a secure and effective Near-duplicate detection (NDD) system over encrypted in-network storage which supported multi-user and multi-key searchable encryption. However, those schemes cannot solve the multi-keyword ranked search problem in the multi-user setting. Therefore, their schemes cannot directly be deployed for addressing our problem. In past approach, Yao et al. proposed multi-source encrypted indexes merge (MEIM) mechanism, where the cloud can merge the encrypted indexes from data owners without knowing the index content. They focused on personal health records, and only considered a numerical “attribute value” for each attribute while ignoring queries on data files that must be built on vectors.
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The Keywords of the Depth of the First Encoding Data on Greedy Algorithm Nube

The Keywords of the Depth of the First Encoding Data on Greedy Algorithm Nube

And on-demand network access to a common set of Configurable computing resources with great efficiency And a minimum of economic overhead [1]. Attracted by this Attractive features, both individuals and companies and Motivated to outsource their data to the cloud, rather than The purchase of hardware and software for data management themselves. In spite of the various advantages of cloud services, Outsourcing sensitive information sources (such as e-mail messages, and personal Health records, financial company data, government Documentation, etc.) to serve remote areas brings privacy concerns. Cloud service providers (CSPs) that keeps Data users have access to sensitive information of users Without a license. General approach to protect Confidentiality of data is to encrypt the data before Outsourcing [2]. However, this leads to a huge cost in Terms of usability data. For example, current technologies On the basis of word retrieval of information, whichUsed widely on the encrypted data can not be directly Applied to the encrypted data. Download all And decoding data from the cloud locally Obviously it is not practical. In order to address the above problem, researchers Some solutions have been designed for general purpose with Fully homomorphic
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