Researchers Poison Stolen Data to Make AI Results Wrong

Researchers poison their own data when stolen by an AI to ruin results

Poisoned knowledge graphs can make the LLM hallucinate, rendering it useless to the thieves.

Researchers poison stolen data to make AI results wrong

: Wanted: Chief Disinformation Officer to pollute company knowledge graphs

Researchers Manipulate Stolen Data To Corrupt AI Models And Generate Inaccurate Outputs - Cybernoz - Cybersecurity News

Researchers from the Chinese Academy of Sciences and Nanyang Technological University have introduced AURA, a novel framework to safeguard proprietary knowledge graphs in GraphRAG systems against theft and private exploitation. Published on arXiv just a week ago, the paper highlights how adulterating KGs with fake but plausible data renders stolen copies useless to attackers while preserving full utility for authorized users.​ Knowledge graphs p…

Automated data poisoning proposed as a solution for AI theft threat

Researchers have developed a tool that they say can make stolen high-value proprietary data used in AI systems useless, a solution that CSOs may have to adopt to protect their sophisticated large language models (LLMs). The technique, created by researchers from universities in China and Singapore, is to inject plausible but false data into what’s known as a knowledge graph (KG) created by an AI operator. A knowledge graph holds the proprietary …

Researchers poison stolen data to make AI systems return wrong results

Wanted: Chief Disinformation Officer to pollute company knowledge graphs Researchers affiliated with universities in China and Singapore have devised a technique to make stolen knowledge graph data useless if incorporated into a GraphRAG AI system without consent. . . .