AI RESEARCH

Good-Enough LLM Obfuscation (GELO)

arXiv CS.LG

ArXi:2603.05035v2 Announce Type: replace-cross Large Language Models (LLMs) are increasingly served on shared accelerators where an adversary with read access to device memory can observe KV caches and hidden states, threatening prompt privacy for open-source models. Cryptographic protections such as MPC and FHE offer strong guarantees but remain one to two orders of magnitude too slow for interactive inference, while static obfuscation schemes break under multi-run statistical attacks once the model is known.