Anomaly Detection for Soft Security in Cloud Based Auditing of Accounting Systems

Mats Neovius, Bob Duncan

Research output: Chapter in Book/Report/Conference proceedingPublished conference contribution

4 Citations (Scopus)
8 Downloads (Pure)

Abstract

Achieving information security in the cloud is not a trivial exercise. When the systems involved are accounting software systems, this becomes much more challenging in the cloud, due both to the systems architecture in use, the challenges of proper configuration, and to the multiplicity of attacks that can be made against such systems. A particular issue for accounting systems concerns maintaining a proper audit trail in order that an adequate level of audit may be carried out on the accounting records contained in the system. In this paper we discuss the implications of the traditional approach to such systems and propose a complementary soft security solution relying on detecting behavioural anomalies by evidence theory. The contribution is in conceptualising the anomalies and providing a somewhat theoretical solution for a difficult and challenging problem. The proposed solution is applicable within any domain consisting of rigorous processes and risk of tampering or data exfiltration, such as the cloud based accounting systems.
Original languageEnglish
Title of host publicationProceedings of the 7th International Conference on Cloud Computing and Services Science
EditorsDonald Ferguson, Victor Méndez Muñoz, Jorge Cardoso, Markus Helfert, Claus Pahl
PublisherSciTePress
Pages499-506
Number of pages8
ISBN (Print)9789897582431
DOIs
Publication statusPublished - 26 Apr 2017
EventThe 7th International Conference on Cloud Computing and Services Science - Holiday Inn Porto Gaia, Porto, Portugal., Porto, Portugal
Duration: 24 Apr 201726 Apr 2017
http://closer.scitevents.org/

Conference

ConferenceThe 7th International Conference on Cloud Computing and Services Science
Abbreviated titleCloser 2017
Country/TerritoryPortugal
CityPorto
Period24/04/1726/04/17
Internet address

Keywords

  • cloud security
  • accounting systems audit
  • anomaly detection

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