Co-Founder and CEO of KYVE Network, Fabian Riewe, gave an exclusive interview to CryptoSlate, where he described how KYVE offers a scalability solution for Web3 by leveraging decentralized data lakes.
KYVE is the first of its kind decentralized data validation protocol that is built on an existing data storage. Leveraging its decentralized protocol to upload data on Arweave, KYVE acts like a validation layer to ensure files uploaded to decentralized storage match the original ones.
While this seems like too much effort for archiving family pictures, Riewe says it is an essential validation step for blockchain archives.
Making data “trustless”
Currently, most data uploading processes happen via a centralized data collector. The centralized actor downloads the data the users want to store and re-uploads it to the storage space. In this case, there is no way of knowing if the centralized actor made any changes or errors to the data or copied it. This concern is where KYVE steps in with a novel solution.
KYVE behaves like the validation layer on top of Arweave, a permanent data storage solution. Instead of using centralized actors to upload the data to Arweave, KYVE leverages its decentralized protocol. Users can upload the data they want to store through KYVE, with no central authority having control or a chance to affect it.
Riewe said this is handy when developers want to store a backup of their blockchains. Riewe explained this by stating:
“Let’s say you’re making a backup of Ethereum, and someone would manipulate just one data point and can completely wreck the whole state that follow [the malicious node]… maybe a few million dollars get missing”
He further continued:
“that’s why it is really important that when loading in the backup, you’re sure that you don’t have to trust the [existing] data anymore… Like making data ‘trustless’”
Solution for all mismatching data problems
In the cases of “non-deterministic” data like the pricing data, Riewe mentioned that KYVE could behave as a guard against oracle attacks where attackers manipulate the price data from outside the protocol’s market.
He described that the protocol could watch the price differences in real time and stop storing data if it exceeds 1%. Instead, the protocol will look for a better matching alternative before starting to store data again.