2008
DOI: 10.14778/1453856.1453875
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Authenticating the query results of text search engines

Abstract: The number of successful attacks on the Internet shows that it is very difficult to guarantee the security of online search engines. A breached server that is not detected in time may return incorrect results to the users. To prevent that, we introduce a methodology for generating an integrity proof for each search result. Our solution is targeted at search engines that perform similarity-based document retrieval, and utilize an inverted list implementation (as most search engines do). We formulate the propert… Show more

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Cited by 69 publications
(51 citation statements)
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“…Besides relational and spatial datasets, authentication of semi-structured and non-structured datasets was studied for streaming data [15,21] and text data [18].…”
Section: Background and Related Workmentioning
confidence: 99%
“…Besides relational and spatial datasets, authentication of semi-structured and non-structured datasets was studied for streaming data [15,21] and text data [18].…”
Section: Background and Related Workmentioning
confidence: 99%
“…The first solution on the authentication of web searches was recently proposed by Pang and Mouratidis in PVLDB 2008 [20]. This work focuses on the specific, but very important and representative case, where search engines perform similarity-based document retrieval.…”
Section: Prior Related Workmentioning
confidence: 99%
“…Inspired by the work by Pang and Mouratidis [20], we propose a new model for performing keyword-search queries over online web contents. In Section 2, we introduce the concept of an authenticated web crawler, an authentication module that achieves authentication of general queries for web searching in a way that is consistent with the current crawling-based search engines.…”
Section: Our Approachmentioning
confidence: 99%
See 1 more Smart Citation
“…Tamassia and Triandopoulos [27] implement a distributed MH-Tree in order to provide data authentication over peer-to-peer networks. The authors in [23] build MH-Trees over inverted indexes [33] in order to guarantee correctness in keyword-based document retrieval.…”
Section: Related Workmentioning
confidence: 99%