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Let's look at software and hardware methods for protecting large language models and neural networks from theft.



Delivery of models together with servers
Installing models on your servers is one of the most effective ways to protect your intellectual property. In Russia, Sber works this way: the company supplies large language models with macedonia whatsapp phone number its servers or data centers, to which clients have no access. Accordingly, it is impossible to download or copy the model.

This option has two serious drawbacks. Firstly, in this case the solution becomes 2-3 times more expensive: the customer has to pay not only for the model, but also for the purchase and maintenance of servers. Secondly, the security service may be against installing third-party servers, to which no one except the vendor will have access.



Hardware encryption
Models can be protected from copying using hardware accelerators and FPGA (Field Programmable Gate Array) and ASIC (Application Specific Integrated Circuit) chips. They are produced by many large technology companies, including NVIDIA, Google, and Alibaba.

These chips are designed and optimized for specific types of AI models, such as convolutional networks for computer vision or transformers for natural language processing.

Another difference is in the presentation of the model. On CPU and GPU, neural networks are loaded into RAM as weights and other information and, accordingly, can be accessed. When loaded onto FPGA or ASIC, the models are implemented at the level of registers and logic gates of the chip.

To get the data stored on them, you have to open the chips, disassemble the chips transistor by transistor, and try to reverse-engineer the model embedded in them.