Resilient Computing Lab
Possible subjects of Bachelor, Master and PhD Theses
The RCL group continuously supports Bachelor, Master and PhD students for their Theses. In general, vast majority of our arguments refer to the field of critical systems i.e., systems whose failure may lead to damage, injuries or economic losses. Some possible research challenges that can be investigated during the Thesis, and contextualixed in their application domains, are reported below.
The list of topics is not exhaustive, and also new topics continuously emerge. The most effective way is to approach members of the RCL groups for updated information.
Safety of machine learning solutions. Machine learning is undeniably an enabling technology in several domains, for example it is at the foundation of autonomous driving. However, unproper (unsafe) behaviour of solutions based on machine learning may lead to dangerous consequences. Many Theses initiatives at the MSc, BSc, and PhD level can be identified in this direction, especially using the autonomous driving as a reference domain, and that may span from the definition of mitigation strategies of possible unsafe behaviours to the comparison of solutions or to their representation and assessment through simulators.
Unsafe object detectors for safe autonomous driving. The purpose is to explore mechanisms to achieve safe autonomous driving in the presence of (unsafe) object detectors. Autonomous driving relies heavily on the output produced by object detectors, for example for trajectory planning. Despite the object detectors may misdetect objects, it is required that the driving task is safe, avoiding hazardous manouvers that may lead to accident. Multiple initiatives at the MSc, BSc, and PhD level can be identified in this direction, especially focused on understanding the impact that misdetection may have to the trajectory planning taks, and architectural or algorithmical solutions to mitigate the impact of misdetection.
Identification of intrusions and failures through monitoring. Monitoring data streams allows detecting attacks as well as possible failures of software or hardware components. In particular, anomaly detection is a machine-learning solution that allows identifying deviations from the expected behaviour; for example, several research works and commercial tools exploit anomaly detection to identify cyber-attacks. Several ideas for possible research can be proposed to interested Students, from the implementation and assessment of algorithms, to their proper tuning and combination with the aim to improve detection scores.
Design, implementation and validation of standard-compliant systems. Critical systems are typically crafted following prescriptions written in standards. The aim of these standards is to enforce on the system specified properties as safety (e.g., ISO 61508 for electronic equipment) or security (e.g., ISA/IEC 62443 for industrial automation and control systems). Since long, there is a constant strive to identify and exercise methodologies, techniques and tools that can provide greater and greater evidence of compliance to the desired properties and at lowered costs. The RCL groups is regularly involved in projects and is in close contact with companies where the design, implementation and evaluation of components is done following such standards, and trying to improve the existing state of the art on methodologies and techniques.
Modeling of Critical Systems.
Modeling is an art, which consists of capturing the important components and relationships of a system while removing unimportant details. Models can be used both for designing a system, and for analyzing its dependability, security, performability properties. Possible topics of Bachelor/Master’s thesis include, but are not limited to: 1) Development/application of Model-Driven-Engineering approaches for modeling and analyzing critical systems; 2) Development/application of stochastic state-based modeling approaches for quantitative assessment of dependability, security, performability attributes of critical systems; 3) Development of methodologies and tools to support the cyber-security risk assessment process of critical systems. Possible topics/technologies involved: UML profiling, languages/tools for Model-to-Model and Model-to-Text transformations (ATL, Viatra, EGL, ...), formalisms for stochastic modeling (SPN, SAN, …), supporting analysis tools (Möbius, …), Game Theory (Stackelberg Security Game).