Gabriel CAMARGO who works in a thesis entitled “A tooled method based on artificial intelligence services for self-protecting software systems” co-supervised with Assoc. Prof. Nicolas HERBAUT (Université Paris 1, France) and Assoc. Prof. Houssem CHEMINGUI (BBS, France).
Estimated period: November 2024 – December 2027.
This project aims to produce an innovative, generic, flexible and tooled method to design and implement self-adaptive systems using the VariaMos framework and able to (i) dynamically detect new attacks or similar future instances of these attacks, (ii) actively diagnose and propose repairing plans (self-healing) with the aim to continue providing quality service in the face of the detected attacks, and (iii) smartly adapt the corresponding system according to the repairing plans.
Oscar AGUAYO who works in a thesis entitled “A tooled approach to automatically build products from software product lines using generative AI capabilities” co-supervised with Assoc. Prof. Samuel SEPULVEDA (Universidad de la Frontera, Chile).
Estimated period: February 2024 – Mars 2027.
This project aims to investigate how the automated product creation approach has been applied through software product lines, identifying challenges, applicable practices, and needs in software engineering. Specifically, this project aims to conceive, implement, and evaluate a framework that uses the generative capabilities of modern artificial intelligence (AI) in the context of software product line engineering to enable the automatic creation and deployment of software products. The main scientific contribution of this project will be to propose a framework that allows software engineers to automatically create a product from a product line using generative AI capabilities.
Andrés LOPEZ who works in a thesis entitled “A tooled method to design and create AI-intensive software product lines” co-supervised with Assoc. Prof. Paola VALLEJO (Univ. EAFIT, Colombia) and Assoc. Prof. Viviana COBALEDA (Universidad de Antioquia, Colombia) .
Estimated period: January 2024 - December 2027.
In this project, we want to study the possibility of software product lines that integrate ML-based components. The project will seek answers to the following questions: do software systems with AI/ML components have particular needs with respect to variability modeling? Which of these needs are not covered by current languages for modeling variability and how to cover them? How could the reusability and configurability needs of AI/ML components be covered in order to derive diverse and varied products from them? How to evaluate the proposed method and what are the results and significance of the evaluation results?
Siler AMADOR who works in a thesis entitled “Cybersecurity reference model to protect critical systems against network attacks in the quantum era” co-supervised with Prof. César PARDO (Universidad del Cauca, Colombia).
Estimated period: January 2022 - December 2025.
The objective of this research is to propose a cybersecurity reference model for operational technology that supports the prevention of network attacks on cyber-physical systems in critical infrastructures before the arrival of the quantum era. This will be achieved through the following essential components applied to critical infrastructures and adapted to the evolution of quantum devices: i) security policy implementation, ii) access control, iii) incident detection and response, iv) risk management, v) cryptography and communication security, and vi) security updates and patches.