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A framework for insider collusion threat prediction and mitigation in relational databases

  • Jordan University of Science and Technology

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

6 Scopus citations

Abstract

This paper proposes a framework for predicting and mitigating insider collusion threat in relational database systems. The proposed model provides a robust technique for database architect and administrators to predict insider collusion threat when designing database schema or when granting privileges. Moreover, it proposes a real time monitoring technique that monitors the growing knowledgebases of insiders while executing transactions and the possible collusion insider attacks that may be launched based on insiders accesses and inferences. Furthermore, the paper proposes a mitigating technique based on the segregation of duties principle and the discovered collusion insider threat to mitigate the problem. The proposed model was tested to show its usefulness and applicability.

Original languageEnglish
Title of host publication2019 IEEE 9th Annual Computing and Communication Workshop and Conference, CCWC 2019
EditorsSatyajit Chakrabarti, Himadri Nath Saha
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages721-727
Number of pages7
ISBN (Electronic)9781728105543
DOIs
StatePublished - 12 Mar 2019
Externally publishedYes
Event9th IEEE Annual Computing and Communication Workshop and Conference, CCWC 2019 - Las Vegas, United States
Duration: 7 Jan 20199 Jan 2019

Publication series

Name2019 IEEE 9th Annual Computing and Communication Workshop and Conference, CCWC 2019

Conference

Conference9th IEEE Annual Computing and Communication Workshop and Conference, CCWC 2019
Country/TerritoryUnited States
CityLas Vegas
Period7/01/199/01/19

Keywords

  • Collusion Threat
  • Data Dependencies
  • Information Security
  • Insider Threat
  • Knowledgebase
  • Relational Database

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