ABSTRACT
Cyberspace is essential for e-business, including small and medium enterprises (SMEs). In reality, SMEs have limited resources for cybersecurity. Furthermore, dealing with the fourth industrial revolution and the post-COVID-19 era, the challenges are not limited to cybersecurity only but also cyber resilience. Over 200 cyber resilience assessment frameworks have been proposed. Thus, SMEs need help to operate cyber resilience as a simple. This paper reviews the technical architectures behind the cyber resilience (CR) to detect processes and monitor assets continuously from incidents in the modeling level. The technical architectures of the CR model are built on five layers. The five layers are services, data, generative models, data analysis, and resilience scale. Machine learning and data mining based a probabilistic model approach works to solve the problem of the CR model. The approach is taken to ensure that the probabilistic model is adaptive in the face of uncertainty. The CR model helps to explain the technical architecture of each layer to realize the probabilistic model in practice. © 2022 IEEE.