Maintaining privacy is the most difficult technical issue with any distributed ledger. The fundamental promise of distributed ledger technology (DLT) is the ability to construct self-reconciling workflows between untrusted participants that maintain integrity across all participants so that a “golden source of truth” can be maintained in perpetuity. This is achieved through two mechanisms: consensus and cryptography. The fundamental challenge associated with maintaining a golden record through consensus is that participants must be able to agree on the state of the network and reject any invalid transactions or unfair play while still respecting the external privacy constraints endowed by the workflows. Simply, participants must be able to agree that something is the same without seeing it. If a consortium network between a German and Swiss bank is set up, any bilateral trades maintained across the network should respect both the data domicile laws. Subsequently, the economic terms and status of the trade should only be accessible across the two entities making the trade.
Adjoint has solved this.
Other solutions such as Hyperledger Fabric, R3 Corda, and Enterprise Ethereum address this issue by ignoring the hard problems and surrendering to the technical difficulty of the problem by jettisoning the core value proposition that made DLT technology promising to start. These technologies do not maintain a true golden record or solve the “trust” problem. Instead, they recreate many independent “channels” or independently synchronized data silos that are expensive and unwieldy to maintain. This is not an improvement on the status quo. Technologies like Hyperledger offer no benefit over traditional database technologies. Technologies like Enterprise Ethereum maintain no privacy at all and instead maintain all transactions in-the-clear such that all participants can view all other participants’ trades at all times.
How has Adjoint solved this?
This may seem like an intractable problem, yet there have been many advances in cryptography and computer science that have allowed us to have our cake and eat it too with regards to privacy. We can separate the maintenance of a global consistency log from the execution of workflows so that only receipts of correct execution are maintained globally through a process known as verifiable computation. In this setup, the two participants act as a prover/verifier pair in a zero-knowledge protocol where the two participants prove to each (in zero-knowledge) that a smart contract workflow has been executed fairly without sharing the private inputs to the contract. The receipt of correct execution is an informationless 16 digit number, which contains no details of the contract details itself, and is added to the global consistency log and checked by all network participants to ensure fair play. This models gives the promises of a fully actualized distributed ledger, eliminates independent data silos, is efficient and cheap to maintain, and respects the complex privacy needs found in financial applications and enterprise environments.