ProMark: Privacy and Transparency-Aware Proximity Advertising Platform

Installation

• Docker@3: https://docs.docker.com/get-docker/
• Docker-Compose@1.28.4: https://docs.docker.com/compose/install/
• python@3.8: https://www.python.org/downloads/
• node.js: https://nodejs.org/en/download/
• Go@1.18: https://go.dev/doc/install
• Hyperledger Fabric@2.2: This project includes the binaries of Hyperledger Fabric@2.2 in the bin folder. If you don't want to use them, feel free to download them from the official Hyperledger Fabric Samples.

Structure

This project includes the following folders & files:

• bin: Hyperledger Fabric binaries.
• config: configurations of Hyperleder Fabric network (core.yaml, configtx.yaml) and digital certificates (crypto-config.yaml). network folder contains the settings of various network architecture.
• docker: docker images for ProMark peers, services (e.g., crypto, log, prometheus), and templates used to generate docker-compose files for various network architecture.
• exp_data: experimental results and figures visualizing the results.
• scripts: base contains scripts to interact with Hyperledger Fabric binaries. The scripts can be used for various Hyperledger Fabric. The remaining scripts in scripts use those in base to deploy ProMark.
• services: this folder is deprecated and will be removed in the next version.
• src: contains ProMark primary source code
  • application (Node.js): contains source codes of the client application that interact with Hyperledger Fabric chaincode (smart contract),
  • chaincodes (Go): contains ProMark chaincodes,
  • caliper (Node.js): contains experimental simulation in Caliper,
  • ext (Go): contains the crypto service,
  • verifier (Go): contains source code of peer verifiers,
  • log (Go): contains log services,
  • visualization (Python): visualizes experimental results.
• docker.py: source code to generate docker-compose files.
• main.sh: the main script to interact with ProMark.
• settings.sh: all ProMark environment variables.

Run the network

All the scripts required to interact with ProMark is in main.sh. However, the simplest way to run ProMark is to restart the whole network and deploy all the chaincodes.

• Restart the network: $./main.sh restart <N_ORGS> <N_PEERS> all, where N_ORGS and N_PEERS are the number of orgnizations per organization type and the number of peers per organization.
• Test all chaincodes: $./main.sh test <N_ORGS> <N_PEERS> to execute the test case that creates campaigns, generates tokens and their one-time versions, and add the token transactions to the ledger.

Run the simulation

The subcommand evaluate in main.sh contains all commands used to evaluate most important chaincodes.

• Evaluate the CreateCampaign chaincode: $./main.sh evaluate <N_ORGS> <N_PEERS> campaign create
• Evaluate the GeneratePoC chaincode: $./main.sh evaluate <N_ORGS> <N_PEERS> proof gen
• Evaluate the GenerateTPoC chaincode: $./main.sh evaluate <N_ORGS> <N_PEERS> proof verifytpoc
• Evaluate the AddCampaignTokenTransaction chaincode: $./main.sh evaluate <N_ORGS> <N_PEERS> proof add

Monitoring

To make it easier to debug ProMark, I created a script to monitor logs of all peers in ProMark network: $./main.sh monitor.

Ports

We export ProMark peers' ports to make it easier to debug ProMark. There are two types of organizations: advertisers (adv) and publisher (pub) with some additional services such as CA, couchdb, verifier,... Their ports can be calcualted as follows:

• Peer <peerId>.<orgType><orgId>.promark.com: orgBasePort + orgId * 100 + peerId * 10, where orgBasePort of advertisers is 5000 and that of publishers is 6000.
• CouchDB of peer <peerId>.<orgType><orgId>.promark.com: Peer port + 1.
• API of peer <peerId>.<orgType><orgId>.promark.com: Peer Port + 2.

docker.py contains source codes to calculate the ports for the docker compose file.

Citation

@ARTICLE{promark,
  author={Hoang, Anh-Tu and Carminati, Barbara and Ferrari, Elena},
  journal={IEEE Transactions on Dependable and Secure Computing}, 
  title={ProMark: Ensuring Transparency and Privacy-Awareness in Proximity Marketing Advertising Campaigns}, 
  year={2024},
  pages={1-12},
  doi={10.1109/TDSC.2024.3478049}}