Introduction
In [13], a security risk assessment method based on an Analytic Hierarchy Process (AHP) model has been introduced. The assessment is carried out using the principles of decomposition, pairwise comparison, and synthesis of weights. AHP employs three layers of decomposition. The first step in AHP is formulating the problem of assessing cloud security risk in a hierarchical structure. In the second level, eight major factors are identified for assessment. In the third level, 39 factors corresponding to higher levels and specific local conditions are identified. The evaluation module uses the constructed AHP tree to assess the system with the help of the judgment matrix, which is filled by cloud experts. Finally, calculating the weighted vectors and getting the final risk order completes the process.
In [14], a hierarchical framework is built to analyze the risk and set the goal for the assessment. An indicator system is then built under each principle, and sub-indicators are introduced for assessment. For example, the first indicator could be the risk of the cloud computing platform, risk of cloud storage, risk of cloud security, and so on. Secondary indicators of cloud platform risk could include the risk of the operating system, risk of application software, and risk of availability.
Risk Assessment Trust Matrix
In [15], the Trust Matrix is used for security risk analysis in cloud environments. Two variables, namely “data cost” and “provider’s history,” are considered. In “data cost,” users can assign a cost to data based on its criticality, whereas “provider’s history” includes the record of the past services provided by the provider to consumers. Additionally, the Cloud Control Matrix (CCM) has been released by the Cloud Security Alliance (CSA) as a baseline security control framework designed to help enterprises assess the risks associated with a cloud provider. The CCM includes a risk management domain to ensure that formal risk assessments are aligned with the enterprise-wide framework, planned and scheduled at regular intervals. This process determines the likelihood and impact of identified risks using qualitative and quantitative methods. Consequently, it facilitates transparency and increases the trust level between the cloud customer and the cloud provider, thereby making cloud a secure environment for the future of business [16].
Quantitative Risk Assessment
In [5], a quantitative risk and impact assessment framework (QUIRC) is introduced to assess six key categories of security objectives (SO): confidentiality, integrity, availability, multi-party trust, mutual auditability, and usability in a cloud computing platform. The impact is determined by subject matter experts who are knowledgeable about the impact of threats on their particular type of business. The quantitative approach enables a more precise measurement of risk by assigning numerical values to the likelihood and impact of various threats.
Qualitative Risk Assessment
The European Network and Information Security Agency (ENISA) [6] has published a guide that allows an informed assessment of the security risks and benefits of using cloud computing. For the purposes of the risk assessment, a medium-sized company was used as a case study to expose all possible information security risks. The risks identified in the assessment are classified into three categories: technical, legal, policy, and organizational issues. Each risk is presented in a table that includes the probability level, impact level, reference to vulnerabilities, reference to affected assets, and the level of risk. The estimation of risk levels is based on ISO/IEC 27005.
Synthesis
After reviewing the literature, several risk assessment methodologies and frameworks have been suggested. The risk assessment methods have been classified into five categories: assessment as a service, quantitative and qualitative, hierarchical, graph analysis, and security matrix assessment. In addition to the risk assessment methods that have been reviewed, the CSA and ENISA lead a number of ongoing research initiatives, such as security guidance, CCM, and STAR.
Despite all these methodologies and initiatives, currently, no complete and concise methodology exists for analyzing and evaluating security risks of cloud-based solutions comprehensively. Cloud-specific threats, vulnerabilities, and risks have already been identified or assessed by numerous sources, but it remains unclear how to assess risks based on Information Risk Management frameworks or methods in the context of the Cloud.
The Need for a Comprehensive Risk Assessment Methodology
The adoption of cloud solutions in several industries has been stalled due to the lack of a comprehensive risk assessment methodology that considers both customer and provider perspectives. Most studies view the problem of assessing security risks either from the cloud customer or the cloud provider perspectives. There is a need for a comprehensive, shared, collaborative, and intelligent risk assessment methodology that considers both customer and provider perspectives.
Such a shared assessment enables the cloud provider to demonstrate how the security risks have been managed and mitigated, as well as enabling the cloud consumer to determine the risk tolerance and define security requirements accordingly. The risk assessment in the cloud computing environment will be more efficient and more autonomous by using intelligent expert agents in our architecture. These agents can facilitate the assessment process by automating data collection, risk evaluation, and mitigation planning, thereby improving the overall security posture of cloud-based systems.
Conclusion
In conclusion, the current methodologies for cloud security risk assessment offer valuable frameworks and tools for identifying and evaluating risks. However, there is still a significant gap in creating a comprehensive, collaborative, and intelligent risk assessment methodology that addresses the needs of both cloud providers and consumers. By leveraging advanced technologies such as intelligent expert agents and integrating quantitative and qualitative assessment methods, we can develop a more robust and effective approach to cloud security risk management. This will not only enhance the security of cloud environments but also build greater trust between cloud providers and consumers, facilitating the broader adoption of cloud solutions across various industries.
References
- [13] Source
- [14] Source
- [15] Source
- [16] Source
- [5] Source
- [6] Source