Top PDF An Efficient Domain and Range Specific Multi keyword Search Method

An Efficient Domain and Range Specific Multi keyword Search Method

An Efficient Domain and Range Specific Multi keyword Search Method

Abstract: A standout amongst the most central administrations of distributed computing is Cloud stockpiling administration. Immense measure of delicate information is put away in the cloud for simple remote get to and to diminish the cost of capacity. It is important to scramble the delicate information before transferring to the cloud server so as to keep up protection and security. The Domain and Range Specific Multi-watchword Search (DRSMS) plan was proposed to minimize the pursuit time and Index storage room. This plan embraces gathering sort strategy to part the record document into D Domains and R Ranges. The Domain depends on the length of the watchword; the Range parts inside the area in light of the primary letter of the catchphrase. A numerical model is utilized to look over the scrambled recorded watchword that takes out the data spillage.
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An Efficient Multi-Keyword Semantic Based Search for Encrypted Cloud Data

An Efficient Multi-Keyword Semantic Based Search for Encrypted Cloud Data

The Semantic Web proposed to simplify the meaning of word by annotating them with metadata. Then by associating metadata to words, semantic searches can be significantly improved as compared to traditional keyword searches. Semantic search[8] allow users to use the natural language word to express what he wants to find. Here the enhanced scheme is proposed for improving documental searches optimized for specific scenarios where user want to search a document but doesn’t remember the exact words used, if plural or singular words were used or if a synonym was used or if antonyms used. The method takes into consideration: 1) the number of direct words of the search queries that are in the document; 2) the number of word variation (plural/singular or different verbs conjugation) of the search query that are in the document; 3) the number of synonyms and also antonyms of the words in the search query that are in the document[2].
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Title: A Review Paper on Implementation of a Secure and Dynamic Multi-Keyword Ranked Search Scheme over Encrypted Cloud Data

Title: A Review Paper on Implementation of a Secure and Dynamic Multi-Keyword Ranked Search Scheme over Encrypted Cloud Data

Abstract— The major aim of this paper is to solve the problem of multi-keyword ranked search over encrypted cloud data at the time of protecting exact method wise privacy in the cloud computing concept in this paper we are using three main parts first one is Data Owner, second one is Data User and third one is cloud computing. In this paper we introduce Implementation of a secure multi-Keyword Ranked search scheme over encrypted cloud data. Specifically, the vector space model and the broadly utilized TF×IDF model are joined as a part of the record development and query generation. We build a unique tree-based file structure and propose "greedy Depth- first Search" calculation to give efficient multi-keyword ranked search with no. of count matching multi-keywords. The protected KNN calculation is used to encrypt the file and query vector. The vector space model facilitates to offer enough search accuracy and the Triple DES encryption used to provide security.
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An Efficient Privacy-Preserving Ranked Keyword Search Method

An Efficient Privacy-Preserving Ranked Keyword Search Method

Y. C. Chang and M. Mitzenmache consider the following problem: a user U wants to store his files in an encrypted form on a remote file server S . Later the user U wants to efficiently retrieve some of the encrypted files containing (or indexed by) specific keywords, keeping the keywords themselves secret and not jeopardizing the security of the remotely stored files. For example, a user may want to store old e-mail messages encrypted on a server managed by Yahoo or another large vendor, and later retrieve certain messages while travelling with a mobile device. In this paper, we offer solutions for this problem under well-defined security requirements. Our schemes are efficient in the sense that no public- key cryptosystem is involved. Indeed, our approach is independent of the encryption method chosen for the remote files. They are also incremental, in that U can submit new files which are secure against previous queries but still searchable against future queries. R. Curtmola, J. Garay, S. Kamara, and R. Ostrovsky studded Searchable symmetric encryption (SSE) allows a party to outsource the storage of his data to another party in a private manner, while maintaining the ability to selectively search over it. This problem has been the focus of active research and several security definitions and constructions have been proposed. In this paper we begin by reviewing existing notions of security and propose new and stronger security definitions. We then present two constructions that we show secure under our new definitions. Interestingly, in addition to satisfying stronger security guarantees, our constructions are more efficient than all previous constructions. Further, prior work on SSE only considered the setting where only the owner of the data is capable of submitting search queries. We consider the natural extension where an arbitrary group of parties other than the owner can submit search queries. We formally define SSE in this multi-user setting, and present an efficient construction.
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Secure and Efficient Multi-keyword Ranked Search Method on Cloud

Secure and Efficient Multi-keyword Ranked Search Method on Cloud

In traditional way we use data encryption to avoid information leakage. However, it is a very challenging task to search on encrypted data as server-side data utilization is more. In order to address the above problem, a general solution with fully- homomorphic encryption has been designed. Searchable encryption schemes allow users to store data in encrypted form and perform search over cypher text domain. Till now numerous works have been proposed under various threat models to perform different search functionality. Among them, multi keyword ranked search has more practical applicability.
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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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Confidentiality Preserving Efficient and Dynamic Multi-Keyword Ranked Search over Encoded Multi Cloud Data

Confidentiality Preserving Efficient and Dynamic Multi-Keyword Ranked Search over Encoded Multi Cloud Data

A general way to deal with secure the information privacy is to scramble the information before outsourcing. Searchable encryption plans empower the customer to store the encoded information to the cloud and execute watchword seek over ciphertext space. As such, bottomless works have been proposed under various danger models to accomplish different inquiry usefulness, for example, single catchphrase pursuit, closeness seek, multi-watchword boolean hunt, positioned look, multi-watchword positioned seek, and so forth. Among them, multi-watchword positioned look accomplishes increasingly consideration for its down to earth pertinence. As of late, some dynamic plans have been proposed to bolster embeddings and erasing operations on archive accumulation. These are critical acts as it is exceptionally conceivable that the information proprietors need to redesign their information on the cloud server.
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An Efficient Search Method over an Encrypted Cloud Data Dipeeka Radke, Nikita Hatwar, Lila Gouda, Minal Shambharkar Parul Gajimwar, Ruchika Raut

An Efficient Search Method over an Encrypted Cloud Data Dipeeka Radke, Nikita Hatwar, Lila Gouda, Minal Shambharkar Parul Gajimwar, Ruchika Raut

cloud. Our system provides the facility that a group of users can query the database provided that they can easily access the data from the cloud anywhere at any time. Our proposed system is able to perform multiple keyword search in a single query and ranks the results so the user can use only the most exact matches in proper order. And set of strict privacy is built according to the requirements. We consider the most effective procedure among number of multi keyword semantics.

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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

The work of past approaches enriched the multi-keyword search. Wang et al., Chuah et al. proposed multi-keyword fuzzy search scheme aimed at the tolerance of Zhang et al. proposed a secure ranked multi-keyword search scheme in a multi-owner model (PRMSM) that not only allows the cloud server to perform a multi-keyword search without knowing any sensitive information, but also enable the data owner to flexibly change the encryption key. However, these schemes rarely focus on query efficiency. Practically, query efficiency is one of the most important indicators of the user experience. Kamara et al. proposed a secure search scheme based on the tree-based index, which can efficiently perform searches. However, it is designed only for a single keyword search. Later, Xu et al. presented an efficient multi-keyword ranked search scheme (MKQE) that enabled a dynamic keyword dictionary and improved the precision of the search. Sun et al. created a privacy-preserving multi-keyword text search scheme. They divided the vector index into multiple layers and proposed a tree-based index structure by applying the MD-algorithm that realized more efficient search functionality, yet resulting in a loss of precision. Xia et al. constructed a tree-based index structure and proposed a greedy depth-first search (GDFS) algorithm that achieved higher search efficiency. Unfortunately, these works don’t consider multiple data owners scenario. Dong et al. considered a practical scenario where multiple users share data via an untrusted third party. To implement it, the authors proposed a novel multi-user searchable data encryption scheme based on proxy cryptography. Different from the existing searchable encryption schemes, their scheme allowed the users to update the shared data set and each user can be reader and writer simultaneously.
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EFFICIENT KEYWORD SEARCH IN RELATIONAL DATABASES

EFFICIENT KEYWORD SEARCH IN RELATIONAL DATABASES

Guoliang Li & et. al (2009), “Progressive Keyword Search in Relational Databases”. In this research Paper database research information retrieval community has recently recognized the benefits of keyword search, we introduce keyword search benefits into relational databases [1]. Lu Qin & et. al (2009), “Scalable Keyword Search on Large Data Streams” In this research Paper is widely realized that the integration of IR (information retrieval) and different database techniques provides users with a wide range of high quality services. We significantly eliminate the number of intermediate outputs when processing joins over a data stream, and therefore can obtain high efficiency [4].
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Enhanced and Efficient Search Multimedia Data by Using Multi Keyword Synonym Query

Enhanced and Efficient Search Multimedia Data by Using Multi Keyword Synonym Query

Proposed system is decentralized system in which distributed nodes work together for data security on cloud by implementing encryption facility , also these nodes manages multi user tasks like sharing , writing data , reading data etc. Due to this decentralized approach keys are managed at different node hence cloud is not having keys for decryption hence data security is assured. Also KDC is not having data hence only encryption keys are not useful to it. Three types of user like owner , writer and reader has respective access control to the data. Hence this system is also manages hierarchical scenarios as far as users role is concern.
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The Implementation of Algorithm to Provide Multikeyword Rank Search Over Encrypted Data

The Implementation of Algorithm to Provide Multikeyword Rank Search Over Encrypted Data

Despite of the various advantages of cloud services, outsourcing sensitive information (such as e-mails, personal health records, company finance data, government documents, etc.) to remote servers brings privacy concerns. The cloud service providers (CSPs) that keep the data for users may access users’ sensitive information without authorization. A general approach to protect the data confidentiality is to encrypt the data before outsourcing [2]. However, this will cause a huge cost in terms of data usability. For example, the existing techniques on keyword-based information retrieval, which are widely used on the plaintext data, cannot be directly applied on the encrypted data. Downloading all the data from the cloud and decrypt locally is obviously impractical. In order to address the above problem, researchers have designed some general-purpose solutions with fully homomorphic encryption [3] or oblivious RAMs [4].
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A SECURE EFFICIENT AND LIGHTWEIGHT ENCRYPTED DATA MATCHING TECHNIQUE FOR MULTI KEYWORD SEARCH IN THE CLOUD

A SECURE EFFICIENT AND LIGHTWEIGHT ENCRYPTED DATA MATCHING TECHNIQUE FOR MULTI KEYWORD SEARCH IN THE CLOUD

Zhangjie Fu et al. [7] described the consumer-centric cloud computing paradigm has been analysed as it is emerged as the development of smart electronic devices combined with the emerging cloud computing technologies. A variety of cloud services are delivered to the consumers with the promise that an effective and efficient cloud search service is achieved. For consumers, they want to find the most relevant products or data, which is highly desirable in the "pay-as-you use" cloud computing paradigm. As sensitive data (such as photo albums, emails, personal health records, financial records, etc.) are encrypted before outsourcing to cloud, traditional keyword search techniques are useless. Meanwhile, existing search approaches over encrypted cloud data support only exact or fuzzy keyword search, but not semantics-based multi-keyword ranked search. Therefore, how to enable an effective searchable system with support of ranked search remains a very challenging problem. This literature proposes an effective approach to solve the problem of multi-keyword ranked search over encrypted cloud data supporting synonym queries. The main contribution of this literature is summarized in two aspects: multi-keyword ranked search to achieve more accurate search results and synonym- based search to support synonym queries. Extensive experiments on real-world dataset were performed to validate the approach, showing that the proposed solution is very effective and efficient for multi keyword ranked searching in a cloud environment.
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Implementation of Efficient Keyword Search in Relational Databases

Implementation of Efficient Keyword Search in Relational Databases

Query processing over graph-structured data is enjoying a growing number of applications. A top-k keyword search query on a graph finds the top k answers according to some ranking criteria, where each answer is a substructure of the graph containing all query keywords. Current techniques for supporting such queries on general graphs suffer from several drawbacks, e.g., poor worst-case performance, not taking full advantage of indexes, and high memory requirements. To address these problems, we propose BLINKS, a bi-level indexing and query processing scheme for top-k keyword search on graphs. BLINKS follow a search strategy with provable performance bounds, while additionally exploiting a bi-level index for pruning and accelerating the search. To reduce the index space, BLINKS partitions a data graph into blocks: The bilevel index stores summary information at the block level to initiate and guide search among blocks, and more detailed information for each block to accelerate search within blocks. Our experiments show that BLINKS offers orders-of-magnitude performance improvement over existing approaches. Categories and Subject Descriptors: H.3.3 [Information Search and Retrieval]: Search process; H.3.1 [Content Analysis and Indexing]: Indexing methods.
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Efficient Location Tracker Using Keyword Search

Efficient Location Tracker Using Keyword Search

ABSTRACT: Special objects specifically locations always associated with one or more keywords related with it. User can reach upto these objects many times with only keywords or at most by using actual co-ordinates of location. While searching multiple locations specifically more places like hotel, theatre, hospital etc. your always gets problem to get all location in one go. If user searches hotel then user will get some hotels near to current location but the decision of which is the best hotel always depends on user. To overcome these problemsby giving suggestion to user on specific parameters and allow user to search more than one places in one go for better user satisfaction.
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A Secure and Dynamic Multi-keyword Ranked Search Scheme over Encrypted Cloud Data

A Secure and Dynamic Multi-keyword Ranked Search Scheme over Encrypted Cloud Data

collection. Goh [8] proposed formal security definitions for SSE and designed a scheme based on Bloom filter. The search time of Goh’s scheme is O (n), where n is the cardinality of the document collection. Curtmola et al. [10] proposed two schemes (SSE-1 and SSE-2) which achieve the optimal search time. Their SSE-1 scheme is secure against chosen-keyword attacks (CKA1) and SSE-2 is secure against adaptive chosen-keyword attacks (CKA2). These early works are single keyword boolean search schemes, which are very simple in terms of functionality. Multi-keyword boolean search allows the users to input multiple query keywords to request suitable documents. Among these works, conjunctive keyword search schemes [15], [16], [17] only return the documents that contain all of the query keywords. Disjunctive keyword search schemes [18], [19] return all of the documents that contain a subset of the query keywords. Predicate search schemes [20], [21], [22] are proposed to support both conjunctive and disjunctive search. All these multikeyword search schemes retrieve search results based on the existence of keywords, which cannot provide
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MapReduce based Method for User Friendly XML Keyword Search

MapReduce based Method for User Friendly XML Keyword Search

A lot of techniques were proposed by the researchers for XML keyword search. Some requires the user to be familiar with XML query languages which is a tedious task for a non-database expert user whereas in some approaches there is no need to have good knowledge in query languages. One of the user friendly methods for XML searching is LCA/ELCA method. A bottleneck for the LCA/ELCA based XML keyword search is that it is not a fast approach. In this paper, we propose a combination of ELCA approach and MapReduce technique for fast and efficient searching. A distributed LCA and ELCA computation method is designed, where each net node computes LCA and ELCA independently and only a little information needs to be transmitted.The paper employs Hadoop as the platform and implements ELCA algorithm in MapReduce framework. As a future work, new MapReduce algorithms can also be combined with other searching techniques like MLCA search techniques, Fuzzy type-ahead searching and so on.
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An Efficient and Privacy Preserving in Multi-          Keyword Ranked Search over Encrypted Cloud Data

An Efficient and Privacy Preserving in Multi- Keyword Ranked Search over Encrypted Cloud Data

The proposed method for the multi keyword ranked search on encrypted data allows not only search but also the dynamic updating information of those files. Here, the data owner is also responsible for the updating information of the information needed for the index generation. So the extra steps are required by the data owner every time he uploads the file to the cloud. But there are many challenges in a secure multi user system i.e. the data owner consider that all the users are trustworthy ad not dishonest. But this is impractical; a dishonest user may lead to many secure problems like sharing the secure key with the unauthorized person or sharing the decrypted data file with another organization. In the future works, we will try to accomplish the challenges for the secure system to improve its privacy...
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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

[17] only returns documents Containing all the main query words. Call contrapuntal Research programs [18] [19] the return of all documents That contains a subset of the query words. Predicate Research programs [20], [21], [22] proposes to support Both associated stratiform and research. All these multikeyword Find retrieve search on the basis of the results of programs On the existence of keywords, which can not provide As a result acceptable positions respectively. Ranked research can enable the quick search more Relevant data. Only send top as the most relevant Documents can effectively reduce network traffic. Some Early works [23], [24], [25] it has realized ranked Search using techniques to maintain order, but it's Designed only to search for a single word. Cao et al. I realized [26] The first-floor maintaining multiple Privacy Grade planned research, in the documents and inquiries Its a carrier the size of a dictionary. With the "Matching Format", are arranged according to the documents For a number of keyword query matching. However, Cao and others in the scheme is not considered The importance of different words, and therefore not Accurate enough. In addition, the efficiency of the search Line chart with the origin of the documents set.
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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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