Risk Assessment Model for Cloud-Connected Networks with Case Study on an Academic Institution
The reliance on cloud services has increased recently, resulting in an abundance of networks connected to these services partially or fully. However, several risks emerge from this action that imposes new challenges. Organizations often maintain a range of services managed in its own local or expanded networks as well as services that could exist on the cloud services sites partially or totally. Organizations have to deal with two types of risks: The first relates to the internal information systems risk of the organization, and the second relates to risks that come with working with cloud services providers. Furthermore, organizations lack benchmarking and references on assessing information systems risks. Most organizations work with vulnerability management concepts rather than risk assessment and mitigation. In this paper, we reformulate strategic e-services in an educational institution as it works between local networks and cloud services at the same time to study the risks associated with them in a hybrid manner. These services are distributed over local network nodes and relevant cloud components. The local network components and nodes; represent hosts with known vulnerability values generated from commercial tools. These vulnerabilities are gathered into vectors with expected impacts and estimate assets value related to these services. Probabilities or risks are identified accordingly. The other component of the research considers analyzing the risk of the cloud services with the computational approach, but it deals with cloud standard components such as data management policies, internal cloud provider management, and internet security. Vulnerability in cloud providers is identified as the compromise of these components and their impact on business continuity. Using vulnerability concepts for both local network and cloud, we introduce a risk probability model for educational organization (e.g.: QOU) services where risks are estimated over Borda Count generated weights for both local network and cloud. Moreover, the overall risk is estimated independently for each component; local network and two clouds. The final step is to investigate the overall risk for the organization. It will be done by prioritizing these risks mutually and analyzing the value of each risk in terms of other risks. For this purpose, we use the analytic hierarchy process (AHP).
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