A New Secure Index Supporting Efficient Index Updating and Similarity Search on Clouds
Title | A New Secure Index Supporting Efficient Index Updating and Similarity Search on Clouds |
Publication Type | Conference Paper |
Year of Publication | 2016 |
Authors | Zhang, Baojia, Zhang, He, Yan, Boqun, Zhang, Yuan |
Conference Name | Proceedings of the 4th ACM International Workshop on Security in Cloud Computing |
Publisher | ACM |
Conference Location | New York, NY, USA |
ISBN Number | 978-1-4503-4285-8 |
Keywords | cloud, cloud computing, Metrics, privacy, pubcrawl, Resiliency, Scalability, similarity search, user privacy, user privacy in the cloud |
Abstract | With the increasing popularity of cloud storage services, many individuals and enterprises start to move their local data to the clouds. To ensure their privacy and data security, some cloud service users may want to encrypt their data before outsourcing them. However, this impedes efficient data utilities based on the plain text search. In this paper, we study how to construct a secure index that supports both efficient index updating and similarity search. Using the secure index, users are able to efficiently perform similarity searches tolerating input mistakes and update the index when new data are available. We formally prove the security of our proposal and also perform experiments on real world data to show its efficiency. |
URL | http://doi.acm.org/10.1145/2898445.2898451 |
DOI | 10.1145/2898445.2898451 |
Citation Key | zhang_new_2016 |