2025-12-23 19:25:30

Is the identification of AI models really that reliable? Most fingerprint recognition experiments are based on an assumption - that the model hosting party is benign and will not actively remove watermarks or identification marks. Sounds quite idealistic.

But what is the reality? In an ecosystem where models are traded, merged, forked, and repackaged, this assumption simply does not hold. Once a model enters the circulation stage, the risk of the identification being tampered with, removed, or even forged sharply increases. Your identification mechanism may perform perfectly in the lab, but in real-world scenarios, it becomes a mere decoration. This is also why model security requires deeper technical design – it cannot rely solely on good-faith assumptions.

View Original

This page may contain third-party content, which is provided for information purposes only (not representations/warranties) and should not be considered as an endorsement of its views by Gate, nor as financial or professional advice. See Disclaimer for details.

16 Likes

Reward
16
5
Repost
Share

Comment

0/400

GasFeeNightmare

· 43m ago

Well, this set of theories is indeed impressive in the lab, but it collapses upon real-world application. Once the model starts circulating, the watermark is long gone, claiming to be identity recognition is just laughable. Perfect laboratory setups = props in real-world scenarios, this statement hits the nail on the head. So, you can't trust that "benevolent assumption" at all, it's too naive. That's why on-chain model verification has never been reliable.

View OriginalReply0

MidnightTrader

· 6h ago

From laboratory perfection to real-world failure, I've seen this script too many times. Model identity recognition is no exception; good-faith assumptions are just a joke in the face of利益.

View OriginalReply0

MemeKingNFT

· 12-23 19:51

The perfect identification mechanism in the laboratory has become a paper tiger on-chain... This logical flaw has been evident for a long time; watermarks cannot be defended against.

View OriginalReply0

TokenSleuth

· 12-23 19:38

Well, this is the old problem of web3, talking about it on paper vs actual combat is completely different. --- Security mechanisms based on good faith assumptions should have died long ago, they are exposed as soon as they are on the chain. --- To put it bluntly, fingerprint recognition is a joke in the fork hell, I stopped believing in this system long ago. --- The lab is perfect until it crashes in the production environment, I've seen this kind of play too many times. --- So the fundamental problem is that the model circulation chain is too complex, and the protection simply can't keep up.

View OriginalReply0

rugged_again

· 12-23 19:34

To put it bluntly, it's just empty talk; once a set of watermarks hits the Secondary Market, its true form is revealed. At the moment of model fork, the identification mark disappears, and everyone knows this. The perfect solution in the lab directly breaks down when faced with the real ecosystem, it's laughable. Relying on protective mechanisms based on goodwill assumptions, how should I put it... it's too naive.

View OriginalReply0