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Ettu: Analyzing Query Intents in Corporate Databases

  • SUNY Buffalo

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

23 Scopus citations

Abstract

Insider threats to databases in the financial sector have become a very serious and pervasive security problem. This paper proposes a framework to analyze access patterns to databases by clustering SQL queries issued to the database. Our system Ettu works by grouping queries with other similarly structured queries. The small number of intent groups that result can then be efficiently labeled by human operators. We show how our system is designed and how the components of the system work. Our preliminary results show that our system accurately models user intent.

Original languageEnglish
Title of host publicationWWW 2016 Companion - Proceedings of the 25th International Conference on World Wide Web
PublisherAssociation for Computing Machinery, Inc
Pages463-466
Number of pages4
ISBN (Electronic)9781450341448
DOIs
StatePublished - Apr 11 2016
Event25th International Conference on World Wide Web, WWW 2016 - Montreal, Canada
Duration: May 11 2016May 15 2016

Publication series

NameWWW 2016 Companion - Proceedings of the 25th International Conference on World Wide Web

Conference

Conference25th International Conference on World Wide Web, WWW 2016
Country/TerritoryCanada
CityMontreal
Period05/11/1605/15/16

Keywords

  • clustering
  • databases
  • insider threats

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