Cloud computing has become the major computational paradigm for the deployment of all kind of applications, ranging from mobile apps to complex AI algorithms. On the other side, the rapid growth of IoT market has led to the need of processing the data produced by smart devices using their embedded resources. The computing continuum paradigm aims at solving the issues related to the deployment of applications across edge-to-cloud cyber-infrastructures.This work considers in-memory data protection to enhance security over the compute continua and proposes a solution for the development of distributed applications that handles security in a transparent way for the developer. The proposed framework has been evaluated using an ML application that classifies health data using a pre-trained model. The results show that securing in-memory data incurs no additional effort at development time and the overheads introduced by the encryption mechanisms do not compromise the scalability of the application.