TRAP@NCI

COS2: Contextual Oblivious Similarity Searching for encrypted data over cloud storage services

Lavnis, Sneha Umesh (2018) COS2: Contextual Oblivious Similarity Searching for encrypted data over cloud storage services. Masters thesis, Dublin, National College of Ireland.

[img]
Preview
PDF (Master of Science)
Download (1MB) | Preview

Abstract

With the development of collaborative storage services, public cloud has picked up force because of their pay-as-you-go billing structure. For the most part, the information archived on the cloud is secured through encryption before outsourcing which makes it had to recover via searching. The search over encrypted cloud approaches flourish to tackle this issue by utilizing cryptographic and indexing procedures to decide the best outcomes. In any case, the vast majority of these approaches utilize exact matching to fulfil the search criteria. In due course, this exact matching conception was expanded by incorporating similarity ranking algorithms. However, this expansion could not succeed in the practical world due to its dependence on third parties to evaluate the search, thus bargaining the privacy of the stored information. Another drawback is that they require extra computational assets and storage resources for search execution, which sets them far behind from a perfect Search Engine. Hence through this research we implement an advance version of similarity search model by (Pervez et al.; 2016)(Pervez et al.; 2017), known as Contextual Oblivious Similarity based Search (COS2). With the proposed system, authorized users can categorize searches resilient to typing errors. Dissimilar to primitive approaches, COS2 introduces browsing caches to better the client experience. Wordnets and Lexicons with dual encryption mechanisms help realizing relevance searches without revealing confidential data on untrusted cloud domains. Finally, this contextual search thrives to reduce the omputational overhead of the overall search procedure.

Item Type: Thesis (Masters)
Subjects: Q Science > QA Mathematics > Electronic computers. Computer science
T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science

T Technology > T Technology (General) > Information Technology > Cloud computing
Divisions: School of Computing > Master of Science in Cloud Computing
Depositing User: CAOIMHE NI MHAICIN
Date Deposited: 23 Oct 2018 15:37
Last Modified: 23 Oct 2018 15:37
URI: http://trap.ncirl.ie/id/eprint/3298

Actions (login required)

View Item View Item