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Home   /   Thesis   /   Dynamic Assurance Cases for Autonomous Adaptive Systems

Dynamic Assurance Cases for Autonomous Adaptive Systems

Computer science and software Cyber security : hardware and sofware Engineering sciences Technological challenges


Providing assurances that autonomous systems will operate in a safe and secure manner is a prerequisite for their deployment in mission-critical and safety-critical application domains. Typically, assurances are provided in the form of assurance cases, which are auditable and reasoned arguments that a high-level claim (usually concerning safety or other critical properties) is satisfied given a set of evidence concerning the context, design, and implementation of a system. Assurance case development is traditionally an analytic activity, which is carried out off-line prior to system deployment and its validity relies on assumptions/predictions about system behavior (including its interactions with its environment). However, it has been argued that this is not a viable approach for autonomous systems that learn and adapt in operation. The proposed PhD will address the limitations of existing assurance approaches by proposing a new class of security-informed safety assurance techniques that are continually assessing and evolving the safety reasoning, concurrently with the system, to provide through-life safety assurance. That is, safety assurance will be provided not only during initial development and deployment, but also at runtime based on operational data.


Département Ingénierie Logiciels et Systèmes (LIST)
Labo.conception des systèmes embarqués et autonomes
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