arXiv (Computer Science - Cryptography and Security) • 13m
Retrieval-Augmented Defense RAD Framework for LLM Jailbreak Prevention
The Retrieval-Augmented Defense (RAD) framework addresses the "security lag" inherent in static LLM safety alignments by shifting defense from model weights to a dynamic retrieval layer. By leveraging Retrieval-Augmented Generation (RAG) to match incoming queries against a curated database of adversarial patterns, RAD mitigates sophisticated jailbreaks such as Prompt Automatic Programming (PAP) and Prompt Automatic Iterative Refinement (PAIR) without requiring costly retraining. This architecture enables "hot-swappable" security updates and provides a controllable mechanism to optimize the trade-off between model utility and safety, as validated by the StrongREJECT benchmark.