Defining and measuring the resilience of network services

Network services are becoming increasingly vital as they now support almost every aspect of society and human life. Due to the high-availability requirements of network service provisioning and the inevitability of the occurrences of security events, the ability of network services to adapt to and/or recover from adverse events and consistently maintain an acceptable level of operations, which is known as resilience, is of utmost importance. However, in information systems, there lacks consensus definition of resilience, and the measurement of which is also in its infancy. To fill this gap, by referring to the concept of resilience in the field of material science, we propose a definition of resilience of network services in terms of the energy released in recovery. Then, by applying neural networks to service status metrics, we construct the state space of network services, which is mathematically a product manifold of a couple of Riemannian manifolds. Finally, based on differential geometry principles, the resilience of network services can be quantified with the behavioral action of resilience mechanisms and the displacement it produces in the state space. Experiment results show that the proposed method is precise in characterizing the resilience of network services and outperforms existing solutions.