Obfuscating the topical intention in enterprise text search
The text search queries in an enterprise can reveal the users' topic of interest, and in turn confidential staff or business information. To safeguard the enterprise from consequences arising from a disclosure of the query traces, it is desirable to obfuscate the true user intention from the se...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Conference Paper |
| Language: | English |
| Published: |
2013
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/99509 http://hdl.handle.net/10220/12980 |
| _version_ | 1824456590508425216 |
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| author | Pang, Hwee Hwa Xiao, Xiaokui Shen, Jiali |
| author2 | School of Computer Engineering |
| author_facet | School of Computer Engineering Pang, Hwee Hwa Xiao, Xiaokui Shen, Jiali |
| author_sort | Pang, Hwee Hwa |
| collection | NTU |
| description | The text search queries in an enterprise can reveal the users' topic of interest, and in turn confidential staff or business information. To safeguard the enterprise from consequences arising from a disclosure of the query traces, it is desirable to obfuscate the true user intention from the search engine, without requiring it to be re-engineered. In this paper, we advocate a unique approach to profile the topics that are relevant to the user intention. Based on this approach, we introduce an (ε1, ε2)-privacy model that allows a user to stipulate that topics relevant to her intention at ε1 level should appear to any adversary to be innocuous at ε2 level. We then present a Top Priv algorithm to achieve the customized (ε1, ε2)-privacy requirement of individual users through injecting automatically formulated fake queries. The advantages of Top Priv over existing techniques are confirmed through benchmark queries on a real corpus, with experiment settings fashioned after an enterprise search application. |
| first_indexed | 2025-02-19T03:56:31Z |
| format | Conference Paper |
| id | ntu-10356/99509 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2025-02-19T03:56:31Z |
| publishDate | 2013 |
| record_format | dspace |
| spelling | ntu-10356/995092020-05-28T07:18:21Z Obfuscating the topical intention in enterprise text search Pang, Hwee Hwa Xiao, Xiaokui Shen, Jiali School of Computer Engineering IEEE International Conference on Data Engineering (28th : 2012 : Washington, D. C., US) DRNTU::Engineering::Computer science and engineering The text search queries in an enterprise can reveal the users' topic of interest, and in turn confidential staff or business information. To safeguard the enterprise from consequences arising from a disclosure of the query traces, it is desirable to obfuscate the true user intention from the search engine, without requiring it to be re-engineered. In this paper, we advocate a unique approach to profile the topics that are relevant to the user intention. Based on this approach, we introduce an (ε1, ε2)-privacy model that allows a user to stipulate that topics relevant to her intention at ε1 level should appear to any adversary to be innocuous at ε2 level. We then present a Top Priv algorithm to achieve the customized (ε1, ε2)-privacy requirement of individual users through injecting automatically formulated fake queries. The advantages of Top Priv over existing techniques are confirmed through benchmark queries on a real corpus, with experiment settings fashioned after an enterprise search application. 2013-08-05T03:22:52Z 2019-12-06T20:08:13Z 2013-08-05T03:22:52Z 2019-12-06T20:08:13Z 2012 2012 Conference Paper https://hdl.handle.net/10356/99509 http://hdl.handle.net/10220/12980 10.1109/ICDE.2012.43 en |
| spellingShingle | DRNTU::Engineering::Computer science and engineering Pang, Hwee Hwa Xiao, Xiaokui Shen, Jiali Obfuscating the topical intention in enterprise text search |
| title | Obfuscating the topical intention in enterprise text search |
| title_full | Obfuscating the topical intention in enterprise text search |
| title_fullStr | Obfuscating the topical intention in enterprise text search |
| title_full_unstemmed | Obfuscating the topical intention in enterprise text search |
| title_short | Obfuscating the topical intention in enterprise text search |
| title_sort | obfuscating the topical intention in enterprise text search |
| topic | DRNTU::Engineering::Computer science and engineering |
| url | https://hdl.handle.net/10356/99509 http://hdl.handle.net/10220/12980 |
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