can you please send me the data flow diagram for "fuzzy keyword search over encrypted data in cloud"
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data flow diagram for fuzzy keyword search over encrypted data in cloud computing
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can you please send me the data flow diagram for "fuzzy keyword search over encrypted data in cloud"
30-06-2015, 02:58 PM
data flow diagram for fuzzy keyword search over encrypted data in cloud computing
ABSTRACT
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. That is,there is no tolerance of minor typos and format inconsistencies which, on the other hand, are typical user searching behavior and happen very frequently. This significant drawback makes existing techniques unsuitable in Cloud Computing as it greatly affects system usability, rendering user searching experiences very frustrating and system efficacy very low. In this paper, for the first time we formalize and solve the problem of effective fuzzy keyword search over encrypted cloud data while maintaining keyword privacy. Fuzzy keyword search greatly enhances system usability by returning the matching files when users’ searching inputs exactly match the predefined keywords or the closest possible matching files based on keyword similarity semantics,when exact match fails. In our solution, we exploit edit distance to quantify keywords similarity and develop an advanced technique on constructing fuzzy keyword sets, which greatly reduces the storage and representation overheads. Through rigorous security analysis, we show that our proposed solution is secure and privacy-preserving, while correctly realizing the goal of fuzzy keyword search.
INTRODUCTION
The overall project deals with fuzzy keyword search on cloud server. As cloud computing technology becomes more mature, organizations and individuals wish to store more sensitive data e.g. personal health records, emails, customer related documents in the cloud. By storing such data in the cloud, the data owners do not have to worry about data storage and maintenance. Furthermore, they can enjoy the increased data availability provided by the cloud servers.In recent years, searchable encryption techniques have been developed to allow users to securely search over encrypted data. These techniques typically build an index for each keyword, and associate that index with the files containing that keyword. Using trapdoors of keywords within the index structure preserve both file content and keyword privacy while allowing data users to conduct keyword searches. However, these existing techniques are overly restrictive because they only allow exact keyword search. Often, users that perform searches have typos in their input strings e.g. typing “deiay”instead of “delay”, or the data format may not be the same e.g. “data-warehousing” versus “data warehousing”. A spell-check mechanism can be used. However, this does not completely solve the problem since it may require additional user interactions to determine the correct word from a list of candidates suggested by the spell-check algorithm. Besides, the spell check algorithm may not be smart enough to differentiate between two actual valid words.
Need
The main goal of this project is to focus on enabling effective yet privacy-preserving fuzzy keyword search in Cloud computing. To the best of our knowledge, we formalize for the first time the problem of effective fuzzy keyword search over encrypted cloud data while maintaining keyword privacy.
Objective
The project objective will be achieved by examining the current approaches to securing data in storage and the way it may be processed by cloud-based applications through the implementation of encryption
1. The key objective of this research is to propose a new cryptographic algorithm that can protect data and its related processing in the cloud applications. Such a scheme should be suitable for implementation in cloud computing environments, since data stored in cloud storage always needs to be retrieved and processed by the application.
2. The security of the processed data against all parties involved such as third and unauthorized parties must be guaranteed since every operation – such as retrieving or processing by cloud-based applications – must be performed in encrypted form. Currently, existing schemes only protect certain levels of processing such as the initial input and final output of the processing, but intermediate data may still be disclosed to unauthorized parties.
3. To return the matching files when users’ searching inputs exactly match the predefined keywords.
4. Searchable encryption using traditional cryptography approaches.
5. To build an index for each keyword, and associate that index with the files containing that keyword.
6. To design search schemes which allow multi-keyword query and provide result similarity ranking for effective data retrieval, instead of returning undifferentiated results
7. To prevent the cloud server from learning additional information from the dataset and the index, and to meet privacy requirements.
CONCLUSION
Personalized web search system, which can learn a user's preference implicitly and then generate the user profile automatically. When the user inputs query keywords, more personalized expansion words are generated by the proposed algorithm, and then these words together with the query keywords are submitted to a popular search engine such as Baidu or Google. These expansion words can help search engines retrieval information for a user according to his/her implicit search intentions, and return different search results to different users who input the same keywords. With the tremendous growth of information available to end users through the Web, search engines come to play ever a more critical role. Nevertheless, because of their general purpose approach, it is always less uncommon that obtained result sets provide a burden of useless pages. Next generation Web architecture, represented by Semantic Web, provides the layered architecture possibly allowing to overcome this limitation. Several search engines have been proposed, which allow to increase information retrieval accuracy by exploiting a key content of Semantic Web resources, that is relations. However, in order to rank results, most of the existing solutions need to work on the whole annotated knowledge base. In this paper we propose a relation-based page rank algorithm to be used in conjunction with Semantic Web search engines that simply relies on information which could be extracted from user query and annotated resource. Relevance is measured as the probability that retrieved resource actually contains those relations whose existence was assumed by the user at the time of query definition.
ABSTRACT
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. That is,there is no tolerance of minor typos and format inconsistencies which, on the other hand, are typical user searching behavior and happen very frequently. This significant drawback makes existing techniques unsuitable in Cloud Computing as it greatly affects system usability, rendering user searching experiences very frustrating and system efficacy very low. In this paper, for the first time we formalize and solve the problem of effective fuzzy keyword search over encrypted cloud data while maintaining keyword privacy. Fuzzy keyword search greatly enhances system usability by returning the matching files when users’ searching inputs exactly match the predefined keywords or the closest possible matching files based on keyword similarity semantics,when exact match fails. In our solution, we exploit edit distance to quantify keywords similarity and develop an advanced technique on constructing fuzzy keyword sets, which greatly reduces the storage and representation overheads. Through rigorous security analysis, we show that our proposed solution is secure and privacy-preserving, while correctly realizing the goal of fuzzy keyword search.
INTRODUCTION
The overall project deals with fuzzy keyword search on cloud server. As cloud computing technology becomes more mature, organizations and individuals wish to store more sensitive data e.g. personal health records, emails, customer related documents in the cloud. By storing such data in the cloud, the data owners do not have to worry about data storage and maintenance. Furthermore, they can enjoy the increased data availability provided by the cloud servers.In recent years, searchable encryption techniques have been developed to allow users to securely search over encrypted data. These techniques typically build an index for each keyword, and associate that index with the files containing that keyword. Using trapdoors of keywords within the index structure preserve both file content and keyword privacy while allowing data users to conduct keyword searches. However, these existing techniques are overly restrictive because they only allow exact keyword search. Often, users that perform searches have typos in their input strings e.g. typing “deiay”instead of “delay”, or the data format may not be the same e.g. “data-warehousing” versus “data warehousing”. A spell-check mechanism can be used. However, this does not completely solve the problem since it may require additional user interactions to determine the correct word from a list of candidates suggested by the spell-check algorithm. Besides, the spell check algorithm may not be smart enough to differentiate between two actual valid words.
Need
The main goal of this project is to focus on enabling effective yet privacy-preserving fuzzy keyword search in Cloud computing. To the best of our knowledge, we formalize for the first time the problem of effective fuzzy keyword search over encrypted cloud data while maintaining keyword privacy.
Objective
The project objective will be achieved by examining the current approaches to securing data in storage and the way it may be processed by cloud-based applications through the implementation of encryption
1. The key objective of this research is to propose a new cryptographic algorithm that can protect data and its related processing in the cloud applications. Such a scheme should be suitable for implementation in cloud computing environments, since data stored in cloud storage always needs to be retrieved and processed by the application.
2. The security of the processed data against all parties involved such as third and unauthorized parties must be guaranteed since every operation – such as retrieving or processing by cloud-based applications – must be performed in encrypted form. Currently, existing schemes only protect certain levels of processing such as the initial input and final output of the processing, but intermediate data may still be disclosed to unauthorized parties.
3. To return the matching files when users’ searching inputs exactly match the predefined keywords.
4. Searchable encryption using traditional cryptography approaches.
5. To build an index for each keyword, and associate that index with the files containing that keyword.
6. To design search schemes which allow multi-keyword query and provide result similarity ranking for effective data retrieval, instead of returning undifferentiated results
7. To prevent the cloud server from learning additional information from the dataset and the index, and to meet privacy requirements.
CONCLUSION
Personalized web search system, which can learn a user's preference implicitly and then generate the user profile automatically. When the user inputs query keywords, more personalized expansion words are generated by the proposed algorithm, and then these words together with the query keywords are submitted to a popular search engine such as Baidu or Google. These expansion words can help search engines retrieval information for a user according to his/her implicit search intentions, and return different search results to different users who input the same keywords. With the tremendous growth of information available to end users through the Web, search engines come to play ever a more critical role. Nevertheless, because of their general purpose approach, it is always less uncommon that obtained result sets provide a burden of useless pages. Next generation Web architecture, represented by Semantic Web, provides the layered architecture possibly allowing to overcome this limitation. Several search engines have been proposed, which allow to increase information retrieval accuracy by exploiting a key content of Semantic Web resources, that is relations. However, in order to rank results, most of the existing solutions need to work on the whole annotated knowledge base. In this paper we propose a relation-based page rank algorithm to be used in conjunction with Semantic Web search engines that simply relies on information which could be extracted from user query and annotated resource. Relevance is measured as the probability that retrieved resource actually contains those relations whose existence was assumed by the user at the time of query definition.
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