Demo: Fabric Private Chaincode
IBM and Intel demonstrate the privacy-enhanced capabilities that the Fabric Private Chaincode (FPC) project brings to Hyperledger Fabric, a popular blockchain framework for the enterprise. Such capabi …
|Demo: Fabric Private Chaincode
|Bruno Vavala (Research Scientist, Intel), Marcus Brandenburger (Researcher, IBM Corp.)
|Hyperledger Global Forum
|Phoenix, AZ, USA
|Mar 2- 6, 2020
IBM and Intel demonstrate the privacy-enhanced capabilities that the Fabric Private Chaincode (FPC) project brings to Hyperledger Fabric, a popular blockchain framework for the enterprise. Such capabilities allow Fabric chaincode to maintain and work on encrypted data, thereby hiding any sensitive information from Fabric Peers and hosting organizations. This enables privacy-sensitive applications such as sealed auctions and analytics over medical data. The demo aims at familiarizing and engaging the audience with FPC as follows.First, it argues that the Fabric framework can be seamlessly augmented with a privacy-enhancement feature through a sound and low-cost mechanism. In particular, it briefly overviews the functional and the security aspects of FPC chaincodes. The former describes how FPC chaincodes are executed on Fabric and how clients can interact with them. This will appear straightforward to Fabric users, since FPC does not modify Fabric’s programming model. The latter guides the audience through sensitive-information flows between clients and chaincodes (in the trusted execution environment), and between chaincodes and the ledger.Second, the demo introduces a concrete system which implements FPC based on Intel SGX. It briefly overviews the FPC code base released in Hyperledger Labs, explaining how developers can integrate it with Fabric. Also, it demonstrates how the system can be used in simulation-mode on non-SGX-capable platform.This allows a larger audience to immediately experiment with the code, while work is in progress to support additional platforms.Third, the demo focuses on an application solving a real-world problem, which could not have been easily addressed by Fabric.