Fully Homomorphic Encryption on Llama 3 model for privacy preserving LLM inference
The applications of Generative Artificial Intelligence (GenAI) and their intersections with data-driven fields, such as healthcare, finance, transportation, and information security, have led to significant improvements in service efficiency and low latency. However, this synergy raises serious concerns regarding the security of large language models (LLMs) and their potential impact on the privacy of companies and users' data. Many technology companies that incorporate LLMs in their services with a certain level of command and control bear a risk of data exposure and secret divulgence caused by insecure LLM pipelines, making them vulnerable to multiple attacks such as data poisoning, pro...
| Authors | Anes Abdennebi, Nadjia Kara, Laaziz Lahlou |
|---|---|
| Primary category | cs.CR |
| Published | 14 April 2026 |
| Last updated at source | 14 April 2026 |
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