Managing gigabytes (2nd ed.): compressing and indexing documents and images
Managing gigabytes (2nd ed.): compressing and indexing documents and images
Attribute-based encryption for fine-grained access control of encrypted data
Proceedings of the 13th ACM conference on Computer and communications security
Over-encryption: management of access control evolution on outsourced data
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Fuzzy keyword search over encrypted data in cloud computing
INFOCOM'10 Proceedings of the 29th conference on Information communications
Achieving secure, scalable, and fine-grained data access control in cloud computing
INFOCOM'10 Proceedings of the 29th conference on Information communications
Secure Ranked Keyword Search over Encrypted Cloud Data
ICDCS '10 Proceedings of the 2010 IEEE 30th International Conference on Distributed Computing Systems
FC'10 Proceedings of the 14th international conference on Financial cryptograpy and data security
Privacy-Preserving Query over Encrypted Graph-Structured Data in Cloud Computing
ICDCS '11 Proceedings of the 2011 31st International Conference on Distributed Computing Systems
Privacy-Aware BedTree Based Solution for Fuzzy Multi-keyword Search over Encrypted Data
ICDCSW '11 Proceedings of the 2011 31st International Conference on Distributed Computing Systems Workshops
Multi-User Private Keyword Search for Cloud Computing
CLOUDCOM '11 Proceedings of the 2011 IEEE Third International Conference on Cloud Computing Technology and Science
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With the development of cloud computing, data owners (businesses and individuals) are motivated to outsource their local complex database systems to public cloud for flexibility and economic savings. But for the consideration of user's privacy, personal data has to be special treatment locally before outsourcing to the cloud server. Considering the large number of data users and documents in cloud, it is crucial for data owner to construct an index for their data collection, which increases the cost of the data owner. Related works focus on the searches on encrypted database but rarely consider the overhead of the index construction for data owner and the extensions of the index. Although traditional index construction methods of information retrieval have been widely studied, direct application of these methods would not be necessarily suitable for our scenario. Thus, enabling an efficient index construction service is of paramount. In this paper, we define and solve the problem of index construction on small business (SBIC). Among various index methods, we choose inverted index method. An inverted index is an index data structure storing a mapping from content to its locations in a set of documents. The purpose of it is to allow fast full text searches.We firstly propose a basic SBIC scheme using Lucene (an open source project for web search engine), and then significantly improve it to meet efficient keyword extraction requirement and multi-type files demand. Thorough analysis design goals(see section 2.3) of proposed schemes is given, extensive experimental results on the dataset further show proposed scheme indeed introduce low overhead on time and space.