How To Mitigate The Enterprise Security Risks Of LLMs

The article discusses the potential security risks associated with the use of Large Language Models (LLMs) in businesses. It highlights three main areas of concern: sharing sensitive data with external LLM providers, the security of the model itself, and unauthorized access to sensitive data that LLMs are trained on. The author suggests that businesses should consider training and running their AI chatbot tools within their own secure environment to mitigate these risks.

The article further emphasizes the importance of model security, as LLMs trained on proprietary data can provide valuable insights into a company's strategy. Unauthorized access to sensitive data is another concern, as LLM-based chatbots can potentially be manipulated to reveal sensitive information. The author concludes by advising businesses to prioritize security when adopting new technologies like LLMs.

Key takeaways:

Large Language Models (LLMs) have the potential to increase productivity in businesses, but they also come with several security risks.
Sharing sensitive data with an external LLM provider can lead to potential data breaches, as seen in the case of Samsung banning the use of ChatGPT and other AI chatbots.
Model security is as important, if not more, than data security, as trained models can provide a blueprint of a company's inner workings and strategies.
Unauthorized access to sensitive data can occur if the right safeguards are not in place, with examples of hackers being able to retrieve credit card information through AI chatbots.

How To Mitigate The Enterprise Security Risks Of LLMs

Key takeaways:

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