3 papers
cs.CR2026
The Phish, The Spam, and The Valid: Generating Feature-Rich Emails for Benchmarking LLMs
Rebeka Toth, Tamas Bisztray, Nils Gruschka
In this paper, we introduce a metadata-enriched generation framework (PhishFuzzer) that seeds real emails into Large Language Models (LLMs) to produce 23,100 diverse, structurally…
cs.CR2025
Sustaining Cyber Awareness: The Long-Term Impact of Continuous Phishing Training and Emotional Triggers
Rebeka Toth, Richard A. Dubniczky, Olga Limonova +1
Phishing constitutes more than 90\% of successful cyberattacks globally, remaining one of the most persistent threats to organizational security. Despite organizations tripling the…
cs.AI2024
Dynamic Intelligence Assessment: Benchmarking LLMs on the Road to AGI with a Focus on Model Confidence
Norbert Tihanyi, Tamas Bisztray, Richard A. Dubniczky +11
As machine intelligence evolves, the need to test and compare the problem-solving abilities of different AI models grows. However, current benchmarks are often simplistic, allowing…