Ontology Based Semantic Web Information Retrieval Enhancing Search Significance

The web contain huge amount of structured as well as unstructured data/information. This varying nature of data may yield a retrieval response that is expected to contain relevant response that is expected to contain relevant as well as irrelevant data while directing search. In order to filter out irrelevance in the search result, numerous methodologies have been used to extract more and more relevant search responses in retrieval. This work has adopted semantic search dealing directly with the knowledge base. The approach incorporates Query pattern evolution and semantic keyword matching with final detail to enhance significance of relevant data retrieval. The proposed method is implemented in open source computing tool environment and the result obtained thereof are compared with that of earlier used methodologies

A Novel Approach For Using Multi-Keyword Ranked Search Scheme Over Encrypted in Secure And Dynamic Cloud Data

— cloud computing have revamped the view of modern information technology which is motivating the data owners to outsource their data to the public cloud server like Amazon, Microsoft Azure, Google Drive, etc. With the help of data outsourcing, the organizations can provide reliable data services to their users without any concerns for the data management overhead. . Normally, CSPs (Cloud Service Providers) take care of the data and its privacy, but there are some of the factors because of which the data privacy and user identity may be violated like an apostate employee, etc. In this way, information proprietors ought to scramble their particular touchy information before outsourcing it to people in general cloud server. Since the information is getting encoded before outsourcing which may influence the execution of some essential information getting to operations like seeking of a report, and so on. Searchable encryption is a cryptographic technique to give security. In writing numerous analysts have been chipping away at creating proficient searchable encryption plans. , we display a protected multi-watchword positioned look conspire over scrambled cloud information, which at the same time underpins dynamic overhaul operations like erasure and addition of records. In particular, the vector space display and the broadly utilized TF×IDF model are consolidated as a part of the file development and question era. We build an exceptional tree-based record structure and propose an "Eager Depth-first Search" calculation to give productive multi-catchphrase positioned look.

Multi-user multi-keyword rank search over encrypted data in arbitrary language

National Research Foundation (NRF) Singapore; AXA Research Fun

A Generic Construction for Verifiable Attribute-based Keyword Search Schemes

Cloud data owners encrypt their documents before outsourcing to provide their privacy. They could determine a search control policy and delegate the ability of search token generation to the users whose attributes satisfy the search control policy. Verifiable attribute-based keyword search (VABKS) where the users can also verify the accuracy of cloud functionality is one of such schemes. In this paper, the first generic construction for VABKS is proposed. To this end, the notion of hierarchical identity-based multi-designated verifier signature (HIB-MDVS) has been introduced and existential forgery under chosen message attack (EF-CMA) is formally defined for its unforgeability. Furthermore, anonymity against chosen identity vector set and chosen plaintext attack (Anon-CIVS-CPA) has been defined as the security definition of hierarchical identity-based broadcast encryption (HIBBE) in a formal way. The proposed construction is built in a modular structure by using HIBBE, HIB-MDVS, and Bloom filter as the building blocks. We prove that the security of proposed construction is based on the unforgeability of HIB-MDVS and the anonymity of HIBBE. Finally, the concept of verifiable ranked keyword search will be introduced and a construction of this primitive will be presented which is based on proposed VABKS

Privacy-aware relevant data access with semantically enriched search queries for untrusted cloud storage services

Privacy-aware search of outsourced data ensures relevant data access in the untrusted domain of a public cloud service provider. Subscriber of a public cloud storage service can determine the presence or absence of a particular keyword by submitting search query in the form of a trapdoor. However, these trapdoor-based search queries are limited in functionality and cannot be used to identify secure outsourced data which contains semantically equivalent information. In addition, trapdoor-based methodologies are confined to pre-defined trapdoors and prevent subscribers from searching outsourced data with arbitrarily defined search criteria. To solve the problem of relevant data access, we have proposed an index-based privacy-aware search methodology that ensures semantic retrieval of data from an untrusted domain. This method ensures oblivious execution of a search query and leverages authorized subscribers to model conjunctive search queries without relying on predefined trapdoors. A security analysis of our proposed methodology shows that, in a conspired attack, unauthorized subscribers and untrusted cloud service providers cannot deduce any information that can lead to the potential loss of data privacy. A computational time analysis on commodity hardware demonstrates that our proposed methodology requires moderate computational resources to model a privacy-aware search query and for its oblivious evaluation on a cloud service provider