Tier 2

Tier 2 verification concept. Patterns learned from Tier 1 device data are used to check new data submissions.

Tier 2 verification validates data by pattern matching. It covers data that does not come straight from the device but still matters to the network. The snippets below are conceptual: they show the shape of the flow, not a shipped SDK API.

Pattern matching process

• Pattern Learning: The system learns and stores patterns of data from registered devices.
• Data Submission: A machine or an external source submits data to the blockchain.
• Pattern Comparison: The submitted data is compared against learned patterns.
• Validation Outcome: Data matching known patterns is marked as Tier 2 verified.

Prerequisites

• A pattern recognition module integrated into the blockchain network.
• A dataset of known patterns from Tier 1 verified devices for comparison.

1. Pattern learning

The blockchain system uses historical Tier 1 verified data to learn and record data patterns associated with each registered machine.

// import necessary libraries and functions
import { fetchTier1Data, patternRecognition } from './utils.js';

const learnPatterns = async () => {
  const tier1Data = await fetchTier1Data();

  // Process and store patterns for each machine
  tier1Data.forEach((dataEntry) => {
    const patterns = patternRecognition(dataEntry);
    storePatterns(dataEntry.machineId, patterns);
  });
};

learnPatterns();

2. Data submission

Data is submitted to the blockchain, potentially originating from external sources or indirectly from machines.

// import necessary libraries and functions
import { submitToBlockchain } from './utils.js';

const submitData = async (data) => {
  // Data submission can be from machines or external sources
  // Data is preprocessed and packaged for submission
  const submissionPackage = preprocessData(data);

  submitToBlockchain(submissionPackage);
};

submitData(externalData);

3. Pattern comparison

When new data is submitted, it is compared against the stored patterns to validate its trustworthiness.

// import necessary libraries and functions
import { retrievePatterns, compareWithKnownPatterns } from './utils.js';

const validateData = async (submittedData) => {
  const knownPatterns = await retrievePatterns(submittedData.machineId);

  // Compare submitted data against known patterns
  const isValid = compareWithKnownPatterns(submittedData, knownPatterns);

  return isValid;
};

4. Validation outcome

Data that matches the stored patterns is marked as Tier 2 verified, indicating a level of trustworthiness, though slightly less than Tier 1 verified data.

// import necessary libraries and functions
import { updateDataStatus } from './utils.js';

const markAsTier2Verified = async (dataId, isValid) => {
  if (isValid) {
    // Update the data status on the blockchain to reflect Tier 2 verification
    updateDataStatus(dataId, 'Tier2Verified');
  } else {
    // Handle unverified data accordingly
    handleUnverifiedData(dataId);
  }
};

// Example usage
markAsTier2Verified(submittedDataId, validationOutcome);

Things to watch

• Keep the pattern recognition module able to handle evolving data patterns.
• Guard against false positives in pattern matching.
• Update the pattern database as new data types and sources appear.