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

A4 Konferenspublikationer

Interna författare/redaktörer

Publikationens författare: Mats Neovius, Bob Duncan
Redaktörer: Donald Ferguson, Víctor Méndez Muñoz, Jorge Cardoso, Markus Helfert, Claus Pahl
Publiceringsår: 2017
Förläggare: SCITEPRESS Science And Technology Publications
Moderpublikationens namn: Proceedings of the 7th International Conference on Cloud Computing and Services Science
Volym: 1
Artikelns första sida, sidnummer: 499
Artikelns sista sida, sidnummer: 506
ISBN: 978-989-758-243-1


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.


Accounting systems audit, Anomaly detection, Cloud Security

Senast uppdaterad 2020-25-02 vid 04:12