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20232025
most citedAttack Atlas: A Practitioner's Perspective on Challenges and Pitfalls in Red Teaming GenAI

1 citations · 3 across the 5 of their papers we have counts for

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cs.CR20251 cited

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…

cs.CR20241 cited

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…

cs.CR2024

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…

cs.CR2024

MoJE: Mixture of Jailbreak Experts, Naive Tabular Classifiers as Guard for Prompt Attacks

Giandomenico Cornacchia, Giulio Zizzo, Kieran Fraser +3

The proliferation of Large Language Models (LLMs) in diverse applications underscores the pressing need for robust security measures to thwart potential jailbreak attacks. These at…

cs.CR20241 cited

Attack Atlas: A Practitioner's Perspective on Challenges and Pitfalls in Red Teaming GenAI

Ambrish Rawat, Stefan Schoepf, Giulio Zizzo +10

As generative AI, particularly large language models (LLMs), become increasingly integrated into production applications, new attack surfaces and vulnerabilities emerge and put a f…

cs.CR20231 cited

Privacy-Preserving Federated Learning over Vertically and Horizontally Partitioned Data for Financial Anomaly Detection

Swanand Ravindra Kadhe, Heiko Ludwig, Nathalie Baracaldo +12

The effective detection of evidence of financial anomalies requires collaboration among multiple entities who own a diverse set of data, such as a payment network system (PNS) and…