Biblio

Nowadays, the domain of Information System (IS) security is closely related to that of Risk Management (RM). As an immediate consequence, talking about and tackling the security of IS imply the implementation of a set of mechanisms that aim to reduce or eliminate the risk of IS degradations. Also, the high cadence of IS evolution requires careful consideration of corresponding measures to prevent or mitigate security risks that may cause the degradation of these systems. From this perspective, an access control service is subjected to a number of rules established to ensure the integrity and confidentiality of the handled data. During their lifecycle, the use or manipulation of Access Control Policies (ACP) is accompanied with several defects that are made intentionally or not. For many years, these defects have been the subject of numerous studies either for their detection or for the analysis of the risks incurred by IS to their recurrence and complexity. In our research works, we focus on the analysis and risk assessment of noncompliance anomalies in concrete instances of access control policies. We complete our analysis by studying and assessing the risks associated with the correlation that may exist between different anomalies. Indeed, taking into account possible correlations can make a significant contribution to the reliability of IS. Identifying correlation links between anomalies in concrete instances of ACP contributes in discovering or detecting new scenarios of alterations and attacks. Therefore, once done, this study mainly contributes in the improvement of our risk assessment model.

The most significant threats to networks usually originate from external entities. As such, the Northbound interface of SDN networks which ensures communication with external applications requires particularly close attention. In this paper we propose the Risk Assessment and Management approach to SEcure SDN (RAMSES). This novel solution is able to estimate the risk associated with traffic demand requests received via the Northbound-API in SDN networks. RAMSES quantifies the impact on network cost incurred by expected traffic demands and specifies the likelihood of adverse requests estimated using the reputation system. Accurate risk estimation allows SDN network administrators to make the right decisions and mitigate potential threat scenarios. This can be observed using extensive numerical verification based on an network optimization tool and several scenarios related to the reputation of the sender of the request. The verification of RAMSES confirmed the usefulness of its risk assessment approach to protecting SDN networks against threats associated with the Northbound-API.