Finding Classification Zone Violations with Anonymized Message Flow Analysis

Michael Meinig, Peter Tröger, Christoph Meinel

Abstract

Modern information infrastructures and organizations increasingly face the problem of data breaches and cyber-attacks. A traditional method for dealing with this problem are classification zones, such as ‘top secret’, ‘confidential’, and ‘unclassified’, which regulate the access of persons, hardware, and software to data records. In this paper, we present an approach that finds classification zone violations through automated message flow analysis. Our approach considers the problem of anonymization for the source event logs, which makes the resulting data flow model sharable with experts and the public. We discuss practical implications from applying the approach to a large governmental organization data set and discuss how the anonymity of our concept can be formally validated.

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Paper Citation


in Harvard Style

Meinig M., Tröger P. and Meinel C. (2019). Finding Classification Zone Violations with Anonymized Message Flow Analysis.In Proceedings of the 5th International Conference on Information Systems Security and Privacy - Volume 1: ICISSP, ISBN 978-989-758-359-9, pages 284-292. DOI: 10.5220/0007352602840292


in Bibtex Style

@conference{icissp19,
author={Michael Meinig and Peter Tröger and Christoph Meinel},
title={Finding Classification Zone Violations with Anonymized Message Flow Analysis},
booktitle={Proceedings of the 5th International Conference on Information Systems Security and Privacy - Volume 1: ICISSP,},
year={2019},
pages={284-292},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007352602840292},
isbn={978-989-758-359-9},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 5th International Conference on Information Systems Security and Privacy - Volume 1: ICISSP,
TI - Finding Classification Zone Violations with Anonymized Message Flow Analysis
SN - 978-989-758-359-9
AU - Meinig M.
AU - Tröger P.
AU - Meinel C.
PY - 2019
SP - 284
EP - 292
DO - 10.5220/0007352602840292