From the 1 of 12 linked papers with an AI index.
12 papers
Learning What to Fail On: Failure-Mode Contextual Bandits for Adversarial Data Curation
Roie Kazoom, Ofir Cohen, Rami Puzis +2
We introduce a failure-aware adversarial retrieval-augmented framework for improving robustness in natural language understanding. Rather than selecting synthetic examples with a f…
(EC)2: Event-Centric Explainability for Cybersecurity Through Multi-Agent LLM Investigations
Neta Kirmayer, David Tayouri, Andrés Murillo +3
The paper presents (EC)2, a multi‑agent framework that uses large language models to generate event‑centric, hypothesis‑driven explanations for cybersecurity alerts, improving anal…
COHORT: Collaborative Orchestration for Hardening via Offensive Replay on Emulated Topologies
Chen Frydman, Aviram Zilberman, Rubin Krief +6
Mitigating an observed adversary in an enterprise network typically takes weeks of expert work: an analyst derives a mitigation tailored to that adversary, validates it without bre…
ConGISATA: A Framework for Continuous Gamified Information Security Awareness Training and Assessment
Ofir Cohen, Ron Bitton, Asaf Shabtai +1
The incidence of cybersecurity attacks utilizing social engineering techniques has increased. Such attacks exploit the fact that in every secure system, there is at least one indiv…
FreakOut-LLM: The Effect of Emotional Stimuli on Safety Alignment
Daniel Kuznetsov, Ofir Cohen, Karin Shistik +2
Safety-aligned LLMs go through refusal training to reject harmful requests, but whether these mechanisms remain effective under emotionally charged stimuli is unexplored. We introd…
LISAA: A Framework for Large Language Model Information Security Awareness Assessment
Ofir Cohen, Gil Ari Agmon, Asaf Shabtai +1
The popularity of large language models (LLMs) continues to grow, and LLM-based assistants have become ubiquitous. Information security awareness (ISA) is an important yet underexp…