Threat Model-based Security Test Case Generation Framework and Tool
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TP311

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    Abstract:

    In recent years, software system security issues are attracting increasing attention. The security threats existing in systems can be easily exploited by attackers. Attackers usually attack systems by using various attacking techniques, such as password brute force cracking, phishing, and SQL injection. Threat modeling is a method of structurally analyzing, identifying, and processing threats. Traditional tests mainly focus on testing code defects, which take place in the late stage of software development. It is not able to well connect the results from early threat modeling and analysis for building secure software. Threat modeling tools in the industry lack the function of generating security tests. In order to tackle this problem, this study proposes a framework that is able to generate security test cases from threat models and designs and implements a tool prototype. In order to facilitate tests, this study improves the traditional attack tree model and performs compliance checks. Test scenarios can be automatically generated from the model. The test scenarios are evaluated according to the probabilities of attack nodes, and the scenarios of the threats with higher probabilities will be tested first. The defense nodes are evaluated, and the defense scheme with higher profit is selected to alleviate the threats, so as to improve the system’s security design. By setting parameters for attack nodes, test scenarios can be specified as test cases. In the early stage of software development, with the inputs of the threats identified by threat modeling, test cases can be generated through this framework and tool to guide subsequent security development and test design, which improves the integration of security technology in software design and development. The case study applies this framework and tool in test generation for very high security risks, which shows their effectiveness.

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付昌兰,张贺,李凤龙,匡宏宇.一种基于威胁模型的安全测试用例生成框架和工具.软件学报,2024,35(10):4573-4603

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History
  • Received:August 28,2022
  • Revised:October 26,2022
  • Adopted:
  • Online: September 27,2023
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