Semantic-Based Compound Keyword Search Over Encrypted Cloud Data

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Semantic-based Compound Keyword Search over Encrypted Cloud Data

Semantic-Based Compound Keyword Search Over Encrypted Cloud Data

Abstract

To access outsourced sensitive data in cloud computing, keyword search over encrypted data is essential. In some circumstances, the keywords that the user searches on are only semantically related to the data, rather than through an exact or fuzzy match. Semantic-based Compound Keyword Search over Encrypted Cloud Data Semantic-based keyword search over encrypted cloud data thus becomes of paramount importance. However, existing schemes usually depend on a global dictionary, which not only affects search results accuracy, but also causes data updating inefficiency.

Introduction

Semantic-Based Compound Keyword Search Over Encrypted Cloud Data In cloud computing, an excessive number of personal or business users outsource their data to cloud storage to enjoy the benefits of “pay-on-demand” services and high computing execution. Users choose to encrypt the data before outsourcing to preserve privacy. Thus, the traditional keyword search can not be executed directly on the encrypted data, which restricts the use of data. Semantic-based keyword search is not only convenient for users, but it also expresses exactly the intentions of users.

System Configuration

H/W System Configuration
Speed                   : 1.1 GHz
RAM                      : 256 MB(min)
Hard Disk              : 20 GB
Floppy Drive          : 1.44 MB
Key Board             : Standard Windows Keyboard
Mouse                  : Two or Three Button Mouse
Monitor                : SVGA
S/W System Configuration

Platform                     :  cloud computing

Operating system       : Windows Xp,7,
Server                       : WAMP/Apache
Working on                : Browser Like Firefox, IE

Conclusion

To extract the semantic information of keywords accurately, we first propose an ontology-based compound concept semantic similarity calculation method (CCSS), which greatly improves the precision of sameness measurement between compound concepts by taking into account compound characteristics and a variety of sources of information in ontology. Low overhead on computation and search accuracy outperforming current schemes.