<p>Cloud storage is a widely used service for both a personal and enterprise demands.
However, despite its advantages, many potential users with sensitive data refrain from
fully using the service due to valid concerns about data privacy. An established solution to
this problem is to perform encryption on the client?s end. This approach, however,
restricts data processing capabilities (e.g. searching over the data). In particular,
searching semantically with real-time response is of interest to users with big data. To
address this, this thesis introduces an architecture for semantically searching encrypted
data using cloud services. It presents a method that accomplishes this by extracting and
encrypting key phrases from uploaded documents and comparing them to queries that
have been expanded with semantic information and then encrypted. It presents an
additional method that builds o? of this and uses topic-based clustering to prune the
amount of searched data and improve performance times for big-data-scale. Results of
experiments carried out on real datasets with fully implemented prototypes show that
results are accurate and searching is e?cient.
| Identifer | oai:union.ndltd.org:PROQUEST/oai:pqdtoai.proquest.com:10286646 |
| Date | 21 December 2017 |
| Creators | Woodworth, Jason W. |
| Publisher | University of Louisiana at Lafayette |
| Source Sets | ProQuest.com |
| Language | English |
| Detected Language | English |
| Type | thesis |
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