Security-Pattern Recognition and Validation

The increasing and diverse number of technologies that are connected to the Internet, such as distributed enterprise systems or small electronic devices like smartphones, brings the topic IT security to the foreground. We interact daily with these technologies and spend much trust on a well-established software development process. However, security vulnerabilities appear in software on all kinds of PC(-like) platforms, and more and more vulnerabilities are published, which compromise systems and their users. Thus, software has also to be modified due to changing requirements, bugs, and security flaws and software engineers must more and more face security issues during the software design; especially maintenance programmers must deal with such use cases after a software has been released. In the domain of software development, design patterns have been proposed as the best-known solutions for recurring problems in software design. Analogously, security patterns are best practices aiming at ensuring security. This thesis develops a deeper understanding of the nature of security patterns. It focuses on their validation and detection regarding the support of reviews and maintenance activities. The landscape of security patterns is diverse. Thus, published security patterns are collected and organized to identify software-related security patterns. The description of the selected software-security patterns is assessed, and they are compared against the common design patterns described by Gamma et al. to identify differences and issues that may influence the detection of security patterns. Based on these insights and a manual detection approach, we illustrate an automatic detection method for security patterns. The approach is implemented in a tool and evaluated in a case study with 25 real-world Android applications from Google Play.