Making Cloud SLAs readily usable in the EU private sector
Security metrics’ importance for the decision making in ICT systems with respect to security has been recognised by organizations such as ENISA , CIS  and NIST . Security metrics have been applied for quantifying the security of network systems though several attack graph-based security metrics (e.g., Idika et al. , Lippman et al. , Ortalo et al. , Pamula et al ), or to measure the degree of trustworthiness of software-intensive systems (e.g., Manadhata et al. , Savola , Wang et al. ).
Functionality & Security assessment
Multiple approaches are emerging to assess the functionality and security of CSPs. Li  presents a framework to compare Cloud providers according to performance indicators. Garg et al  use the Analytic Hierarchy Process (AHP) to rank providers based also on performance data to measure various Quality of Service (QoS) attributes. A framework of critical characteristics and measures that enable comparison of Cloud services is also presented in  by Siegel at al. With respect to security assessment presented by Almorsy et al. , the authors propose the notion of evaluating Cloud secSLAs, by introducing a metric to benchmark the security of a CSP based on categories. However, the resulting security categorization is purely qualitative. In Casola et al () a methodology for evaluating and comparing security SLAs expressed through the use of standard policy languages is presented. Luna  uses a similar approach to quantify the security of a Public Key Infrastructure, based on its Certificate Policy. In  Ghani et al. present a metric-based approach for assessing the security level of Critical Infrastructures.
Security metrics in SLAs
Security metrics are also used for the definition of SLAs. In , Luna et al. point to the need of developing a security metrics framework for the Cloud. Other security-metrics based approach propose mechanisms to describe and quantify security are given in  by Breier et al. Few works focus on security metrics aggregation in order to enable the quantification of the security level in the end-to-end of all collaborators of the supply chain. Unfortunately, metrics aggregation mostly remains a research challenge as acknowledged by NIST  and ENISA . Very few frameworks have been proposed to aggregate security metrics. Among them are the works done by Massacci et al. , Frankova et al. , Seamons et al.  and Smith et al. . Predictive approaches for anticipating how security metrics will develop have been also studied and applied (e.g., Trust Economics system modelling paradigm ,  and the ADVISE modelling approach of .
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