Integrating OSCTI into Self-adaptive Systems
| Typ | Bachelorarbeit | |
|---|---|---|
| Aushang | Bachelor OSCTI for SAS develpment.pdf | |
| Betreuer | Wenden Sie sich bei Interesse oder Fragen bitte an: Lin Cui (E-Mail: lin.cui@kit.edu), Raffaela Mirandola (E-Mail: raffaela.mirandola@kit.edu) |
Motivation
Self-adaptive systems (SAS) are designed to autonomously adjust their behavior in response to dynamic changes in external environments or internal system states. Their interaction with unpredictable, open environments significantly broadens their attack surfaces, making them highly vulnerable to threats. However, SAS is widely utilized in critical domains such as autonomous driving, manufacturing, energy, healthcare, critical infrastructure, etc., where any compromise can lead to catastrophic consequences. Recognizing the paramount importance of safeguarding SAS and the rapid evolution of threats, this thesis aims to provide the dynamically adaptive SAS with real-time threat information acquisition capability by integrating an automated Open Source Cyber Threat Intelligence (OSCTI, real-time updatable open-source information about potential or existing cyber threats) mining pipeline into the SAS Knowledge base. By contributing, you can establish a specialized information interface and lay a foundation for the comprehensive advancement of security protection methodologies within the SAS framework. Additionally, you can enhance your expertise in SAS and security, and develop practical problem-solving skills for real-world industry challenges.
Tasks
- Investigate sources of OSCTI.
- Develop a OSCTI mining pipeline into the Knowledge base of SAS based on existing codes.
- Evaluate the pipeline's performance.
Tools/Technology
- Python, CTI, Natural language processing (NLP), Machine Learning
Benifits
- Working with cutting-edge and innovative technologies
- Close connection to on-going/current research project
- Very good working environment and intensive support