Towards a model-driven engineering approach for trusted execution environments

As digital cities evolve, the integration of diverse services becomes critical. However, the challenge lies not so much in traditional integration platforms such as Apache Camel or Mule, but in environments in which these platforms are deployed, which may lack mechanisms to guarantee the privacy and...

Full description

Autores:
Jáuregui Rozo, Juan Manuel
Tipo de recurso:
Trabajo de grado de pregrado
Fecha de publicación:
2025
Institución:
Universidad de los Andes
Repositorio:
Séneca: repositorio Uniandes
Idioma:
eng
OAI Identifier:
oai:repositorio.uniandes.edu.co:1992/76223
Acceso en línea:
https://hdl.handle.net/1992/76223
Palabra clave:
Trusted Execution Environment
Morello Board
CHERI
Model-Driven Engineering
Code Generation
Sirius
Acceleo
Digital Cities
Secure Integration
Ingeniería
Rights
openAccess
License
Attribution 4.0 International
Description
Summary:As digital cities evolve, the integration of diverse services becomes critical. However, the challenge lies not so much in traditional integration platforms such as Apache Camel or Mule, but in environments in which these platforms are deployed, which may lack mechanisms to guarantee the privacy and integrity of the data. Trusted Execution Environments (TEEs) offer secure compartments in memory for the execution of code and processing of sensitive data, providing stronger protection against attacks. Among these TEE, the Morello Board has the capabilities for compartmentalized execution using the CHERI architecture. Despite its potential, development for the Morello platform is hindered by the complexity of writing secure code in C. To address this, we propose a model-driven approach that enables automatic generation of code in C for TEEs. Our methodology includes the definition of a metamodel and model using Sirius and code generation using Acceleo. This generated code is compatible with the Morello Board. Furthermore, we demonstrate the feasibility of this approach using a case study focused on the integration of secure services in the context of smart cities.