With the constant evolution of hardware architecture extensions aimed at enhancing software security, a notable availability gap arises due to the proprietary nature and design-specific characteristics of these features, resulting in a CPU-specific implementation. This gap particularly affects low-end embedded devices that often rely on CPU cores with limited resources. Addressing this challenge, this thesis focuses on providing access to hardware-based Trusted Execution Environments (TEEs) for devices lacking TEE support. RSGX is a framework crafted to transparently offload security-sensitive workloads to an enclave hosted in a remote centralized edge server. Operating as clients, low-end TEE-lacking devices can harness the hardware security features provided by TEEs of either the same or different architecture. RSGX is tailored to accommodate applications developed with diverse TEE-utilizing SDKs, such as the Open Enclave SDK, Intel SGX SDK, and many others. This facilitates easy integration of existing enclave-based applications, and the framework allows users to utilize its features without requiring any source code modifications, ensuring transparent offloading behind the scenes. For the evaluation, we set up an edge computing environment to execute C/C++ applications, including two overhead micro-benchmarks and four popular open-source applications. This evaluation of RSGX encompasses an analysis of its security benefits and a measurement of its performance overhead. We demonstrate that RSGX has the potential to mitigate a range of Common Vulnerability Exposures (CVEs), ensuring the secure execution of confidential computations on hybrid and distributed machines with an acceptable performance overhead. / Master of Science / A vast amount of data is generated globally every day, most of which contains critical information and is often linked to individuals. Therefore, safeguarding data is essential at every stage, whether it's during transmission, storage, or processing. Different security principles are applied to protect data at various stages. This thesis particularly focuses on data in use. To protect data in use, several technologies are available, and one of them is confidential computing, which is a hardware-based security technology. However, confidential computing is limited to certain high-end computing machines, and many resource-constrained devices do not support it. In this thesis, we propose RSGX, a framework to offload secured computation to a confidential computing-capable remote device with a Security as a Service (SECaaS) approach. Through RSGX, users can leverage confidential computing capabilities for any of their applications based on any SDK. RSGX provides this capability transparently and securely. Our evaluation shows that users, by adapting RSGX, can mitigate several security vulnerabilities, thereby enhancing security with a reasonable overhead.