Fraunhofer-Gesellschaft

Publica

Hier finden Sie wissenschaftliche Publikationen aus den Fraunhofer-Instituten.

MERCAT: A Metric for the Evaluation and Reconsideration of Certificate Authority Trustworthiness

 
: Heinl, Michael P.; Giehl, Alexander; Wiedermann, Norbert; Plaga, Sven; Kargl, Frank

:

Association for Computing Machinery -ACM-; Association for Computing Machinery -ACM-, Special Interest Group on Security, Audit and Control -SIGSAC-:
CCSW 2019, ACM SIGSAC Conference on Cloud Computing Security Workshop. Proceedings : November 11, 2019, London
New York: ACM, 2019
ISBN: 978-1-4503-6826-1
pp.1-15
Conference on Cloud Computing Security Workshop (CCSW) <2019, London>
English
Conference Paper
Fraunhofer AISEC ()
cloud security; metric; Ca; trustworthiness assessment; PKI; Digital Certificate; X.509

Abstract
Public key infrastructures (PKIs) build the foundation for secure communication of a vast majority of cloud services. In the recent past, there has been a series of security incidents leading to increasing concern regarding the trust model currently employed by PKIs. One of the key criticisms is the architecture's implicit assumption that certificate authorities (CAs) are trustworthy a priori. This work proposes a holistic metric to compensate this assumption by a differentiating assessment of a CA's individual trustworthiness based on objective criteria. The metric utilizes a wide range of technical and non-technical factors derived from existing policies, technical guidelines, and research. It consists of self-contained submetrics allowing the simple extension of the existing set of criteria. The focus is thereby on aspects which can be assessed by employing practically applicable methods of independent data collection. The metric is meant to help organizations, individuals, and service providers deciding which CAs to trust or distrust. For this, the modularized submetrics are clustered into coherent submetric groups covering a CA's different properties and responsibilities. By applying individually chosen weightings to these submetric groups, the metric's outcomes can be adapted to tailored protection requirements according to an exemplifying attacker model.

: http://publica.fraunhofer.de/documents/N-572098.html