Today, cryptocurrencies are mostly traded on centralized exchanges, which can handle very large bid volumes very quickly at low costs. However, the trader risks the total loss of his deposited tokens in case of a hacker attack or fraud of the operator.

Alternatively, decentralized exchanges are becoming increasingly popular. These consist of smart contracts that are available on different blockchains. The trader thus always retains sovereignty over his tokens. Unfortunately, decentralization comes at a painful price: fees increase rapidly as demand grows, and clearing takes at least a few seconds.

PolkaDEX combines the best of both worlds: Fast trade execution thanks to an off-chain matching engine combined with trusted execution to manage balances. This ensures that the exchange operator (or a hacker) cannot dispose of the credits at any time without a matching bid from the owner.

PolkaDEX and SCS are working together on this solution using SubstraTEE, the open source framework developed by SCS to develop publicly auditable solutions with trusted execution.

Together with our client, the Web3 Foundation, we’ve published a blog about our trusted off-chain computing platform SubstraTEE which improves confidentiality, scalability and interoperability of blockchain solutions:

Have a TEE with Polkadot

More technical detail and a live demo with private token transactions is given in the recording of our recent meetup:

This project is open source and the code is available on GitHub

Industrial applications require an increasing degree of trust and privacy protection. Proof of existence, of origination or of a consistent track record gain importance. Trusting the timestamps and the integrity of sensor data can be a crucial requirement, i.e. for using surveillance camera footage as evidence in court.

SCS has set up an infrastructure that proves a concept to add trusted timestamps to sensor data based on a public blockchain. This allows to prove that (sensor) data has been captured at a specific point in time. Such a proof includes existence at certain time as well as prior inexistence, with a time precision of minutes. While it has previously been possible to prove that data existed before a certain point in time, this concept show a way to also prove that data only existed after
a certain point in time.

Please read our whitepaper:

trusted-sensor-whitepaper