Researchers Manipulate Stolen Data to Corrupt AI Models and Generate Inaccurate Outputs

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 […] The post Researchers Manipulate Stolen Data to Corrupt AI Models and Generate Inaccurate Outputs appeared first on Cyber Security News.