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

Mats Neovius, Bob Duncan

Research output: Chapter in Book/Conference proceedingConference contributionScientificpeer-review

4 Citations (Scopus)

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 exfiltrat ion, such as the cloud based accounting systems.

Original languageUndefined/Unknown
Title of host publicationProceedings of the 7th International Conference on Cloud Computing and Services Science
EditorsDonald Ferguson, Víctor Méndez Muñoz, Jorge Cardoso, Markus Helfert, Claus Pahl
PublisherSCITEPRESS Science And Technology Publications
Pages499–506
ISBN (Print)978-989-758-243-1
DOIs
Publication statusPublished - 2017
MoE publication typeA4 Article in a conference publication
EventInternational Conference on Cloud Computing and Services Science (CLOSER) - Proceedings of the 7th International Conference on Cloud Computing and Services Science (CLOSER 2017)
Duration: 24 Apr 201726 Apr 2017

Conference

ConferenceInternational Conference on Cloud Computing and Services Science (CLOSER)
Period24/04/1726/04/17

Keywords

  • Accounting systems audit
  • Anomaly detection
  • Cloud Security

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