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Developers have a core requirement for on-chain computation: how to solve the trust issue? The answer lies in the Trusted Execution Environment (TEE) solution.
In simple terms, TEE runs code in an encrypted isolated sandbox. Your input data is protected by encryption, you can see the code logic before execution, and after completion, you can obtain the signed result. Most importantly—raw data will never be leaked outside.
This way, on-chain computation can ensure privacy while making results verifiable. Whether it's off-chain processing or cross-chain interactions, this trust mechanism can be used to ensure data security. $RLC is using this approach to reshape the ecosystem of on-chain privacy computing.
RLC playing in this direction is correct; the privacy computing ecosystem should indeed be developed this way.
It's basically outsourcing trust to hardware. Not sure if it will become the next attack point.
How far $RLC can go on this path is really hard to say; we've been talking about privacy computing for so many years.
Isolation sandbox sounds good, but what really makes me skeptical is how well this thing performs.
It always feels like encryption and privacy are caught in a constant tug-of-war between pursuit and compromise.
Wait, are you sure the data will never be leaked? Can you trust the hardware layer?
$RLC has been in this space quite early. How is the ecosystem implementation going?
Honestly, just shouting slogans about data privacy is useless; it needs to be genuinely verifiable. If $RLC can really do a good job with this, then it's worth paying attention to.