A Model-based Mode-switching Framework based on Security Vulnerability Scores
Sprache des Vortragstitels:
38th IEEE/ACM International Conference on Automated Software Engineering (ASE 2023), Kirchberg, Luxemburg, September 11-15, 2023
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Software vulnerabilities can affect critical systems within an organization impacting processes, workflows, privacy, and safety. When a software vulnerability becomes known, affected systems are at risk until appropriate updates become available and eventually deployed. This period can last from a few days to several months, during which attackers can develop exploits and take advantage of the vulnerability. It is tedious and time-consuming to keep track of vulnerabilities manually and perform necessary actions to shut down, update, or modify systems. Vulnerabilities affect system components, such as a web server, but sometimes only target specific versions or component combinations.
In this paper, we propose a novel approach for automated mode switching of software systems to support system administrators in dealing with vulnerabilities and reducing the risk of exposure. We rely on model-driven techniques and use a multi-modal architecture to react to discovered vulnerabilities and provide automated contingency support. We have developed a dedicated domain-specific language to describe potential mitigation as mode switches. We have evaluated our approach with a web server case study, analyzing historical vulnerability data. Based on the vulnerabilities scores sum, we demonstrated that switching to less vulnerable modes reduced the attack surface in 98.9% of the analyzed time.