Penetration testing is widely used in industry as a test method for web application security assessment. However, penetration testing is often performed late in a software development life cycle as an isolated task and usually requires specialized security experts. There is no well-defined test framework providing guidance and support to general testers who usually do not have in-depth security expertise to perform a systematic and cost-efficient penetration test campaign throughout a security-oriented software development life cycle.
In this thesis, we propose a model-driven penetration test framework for web applications that consists of a penetration test methodology, a grey-box test architecture, a web security knowledge base, a test campaign model, and a knowledge-based PenTest workbench. The test framework enables general testers to perform a penetration test campaign in a model-driven approach that is fully integrated into a security-oriented software development life cycle. Security experts are still required to build up and maintain a web security knowledgebase for test campaigns, but the general testers are capable of developing and executing penetration test campaigns with reduced complexity and increased reusability in a systematic and cost-efficient approach.
A prototype of the framework has been implemented and applied to three web applications: the benchmark WebGoat web application, a hospital adverse event management system (AEMS), and a palliative pain and symptom management system (PAL-IS). An evaluation of the test framework prototype based on the case studies indicates the potential of the proposed test framework to improve how penetration test campaigns are performed and integrated into a security-oriented software development life cycle.
Identifer | oai:union.ndltd.org:uottawa.ca/oai:ruor.uottawa.ca:10393/20552 |
Date | January 2012 |
Creators | Xiong, Pulei |
Contributors | Peyton, Liam |
Publisher | Université d'Ottawa / University of Ottawa |
Source Sets | Université d’Ottawa |
Language | English |
Detected Language | English |
Type | Thesis |
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