| Project Detail |
More secure web applications with privacy incorporated
The application of standard business practices to building software applications is advancing rapidly to meet the evolving needs of web-based application software powered by artificial intelligence (AI). The EU-funded TESTABLE project proposes a software development lifecycle (SDLC) that combines two metrics to quantify the security and privacy risks of a program: the code testability and vulnerable behaviour indicators. TESTABLE will empower software/AI developers, managers, testers, and auditors to reduce the risk by building better security and privacy testing techniques for web applications and removing or mitigating the impact of the patterns causing the high-risk levels. It will develop algorithms, techniques, and tools to analyse, test, and study web applications.
"TESTABLE addresses the grand challenge of building and maintaining modern web-based and AI-powered application software secure and privacy-friendly. TESTABLE intends to lay the foundations for a new integration of security and privacy into the software development lifecycle (SDLC), by proposing a novel combination of two metrics to quantify the security and privacy risks of a program, i.e. the code testability and vulnerable behavior indicators. Based on the novel concept of ""testability patterns,"" TESTABLE will empower the SDLC actors (e.g. software/AI developers, managers, testers, and auditors) to reduce the risk by building better security and privacy testing techniques for classical and AI-powered web applications, and removing or mitigating the impact of the patterns causing the high-risk levels.
To achieve these goals, TESTABLE will develop new algorithms, techniques, and tools to analyze, test, and study web-based application software. First, TESTABLE will deliver algorithms and techniques to calculate the risk levels of the web applications code. Second, TESTABLE will provide new testing techniques to improve software testability. It will do so with novel static and dynamic program analysis techniques by tackling the shortcomings of existing approaches to detect complex and hard-to-detect web vulnerabilities, and combining ideas from the security testing and adversarial machine learning fields. TESTABLE will also pioneer the creation of a new generation of techniques tailored to test and study privacy problems in web applications. Finally, TESTABLE will deliver novel techniques to assist software/AI developers, managers, testers, and auditors to remove or mitigate the patterns associated with the high risk.
TESTABLE relies on a long-standing team of nine European partners with strong expertise in security testing, privacy testing, machine learning security, and program analysis, and who strive for excellence with a proven strong track record and impact in the security communities." |
