2025 IEEE International Conference on Cyber Security and Resilience

Full Program

Summary:

Cyber Threat Intelligence (CTI) enables organisations and individuals to gather knowledge about the cyber-attack landscape. This work presents a framework CTI-GEN for generating CTI in the Structured Threat Information eXpression (STIX) format from unstructured textual reports. The framework leverages Large Language Models (LLMs) to automate the generation of CTI in STIX. The framework consists of six components each designed to complement and correct the previous ones and uses detailed prompt engineering procedures to guide the model in generating CTI in STIX. To this end the STIX schema was preprocessed to simplify its complex and redundant interdependencies so that to be leveraged it effectively. CTI-GEN achieved an F1-Score of 81\% in generating relevant objects from the text 57\% in the generation of relationships between the objects and importantly a precision of 96\% in the assignment of values to attributes in the CTI objects. This work presents the first approach to generate.

Author(s):

Angelos Papoutsis    
Information Technologies Institute, Centre for Research and Technology Hellas (CERTH), Thessaloniki, Greece
Greece

Athanasios Dimitriadis    
Information Technologies Institute, Centre for Research and Technology Hellas (CERTH), Thessaloniki, Greece
Greece

Dimitris Kavallieros    
Information Technologies Institute, Centre for Research and Technology Hellas (CERTH), Thessaloniki, Greece
Greece

Theodora Tsikrika    
Information Technologies Institute, Centre for Research and Technology Hellas (CERTH), Thessaloniki, Greece
Greece

Stefanos Vrochidis    
Information Technologies Institute, Centre for Research and Technology Hellas (CERTH), Thessaloniki, Greece
Greece

Ioannis Kompatsiaris    
Information Technologies Institute, Centre for Research and Technology Hellas (CERTH), Thessaloniki, Greece
Greece

Georgios Meditskos    
School of Informatics, AUTH
Greece

 


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