5 papers
Adversarial Prompt Evaluation: Systematic Benchmarking of Guardrails Against Prompt Input Attacks on LLMs
Giulio Zizzo, Giandomenico Cornacchia, Kieran Fraser +7
As large language models (LLMs) become integrated into everyday applications, ensuring their robustness and security is increasingly critical. In particular, LLMs can be manipulate…
Towards Assurance of LLM Adversarial Robustness using Ontology-Driven Argumentation
Tomas Bueno Momcilovic, Beat Buesser, Giulio Zizzo +2
Despite the impressive adaptability of large language models (LLMs), challenges remain in ensuring their security, transparency, and interpretability. Given their susceptibility to…
Knowledge-Augmented Reasoning for EUAIA Compliance and Adversarial Robustness of LLMs
Tomas Bueno Momcilovic, Dian Balta, Beat Buesser +2
The EU AI Act (EUAIA) introduces requirements for AI systems which intersect with the processes required to establish adversarial robustness. However, given the ambiguous language…
Towards Assuring EU AI Act Compliance and Adversarial Robustness of LLMs
Tomas Bueno Momcilovic, Beat Buesser, Giulio Zizzo +2
Large language models are prone to misuse and vulnerable to security threats, raising significant safety and security concerns. The European Union's Artificial Intelligence Act see…
Developing Assurance Cases for Adversarial Robustness and Regulatory Compliance in LLMs
Tomas Bueno Momcilovic, Dian Balta, Beat Buesser +2
This paper presents an approach to developing assurance cases for adversarial robustness and regulatory compliance in large language models (LLMs). Focusing on both natural and cod…