Pattern Recognition

Advanced pattern recognition capabilities for blockchain transaction analysis.

Overview

The pattern recognition system uses machine learning algorithms to identify recurring patterns in blockchain transactions, helping to detect trends, behaviors, and potential security issues.

Core Features

Transaction Patterns

  • Recurring Transactions: Detection of regular payment patterns
  • Batch Transactions: Identification of grouped transaction behaviors
  • Temporal Patterns: Time-based transaction analysis
  • Address Clustering: Related address pattern identification

Machine Learning Models

pub struct PatternRecognizer {
    pub model: Box<dyn MLModel>,
    pub feature_extractor: FeatureExtractor,
    pub threshold: f64,
}

impl PatternRecognizer {
    pub async fn analyze_pattern(&self, transactions: &[Transaction]) -> Result<PatternAnalysis, Error> {
        let features = self.feature_extractor.extract(transactions)?;
        let prediction = self.model.predict(&features).await?;

        Ok(PatternAnalysis {
            pattern_type: self.classify_pattern(&prediction),
            confidence: prediction.confidence,
            features: features,
        })
    }
}

Pattern Types

1. Financial Patterns

  • Payment Schedules: Regular payment intervals
  • Salary Payments: Employment-related transaction patterns
  • Bill Payments: Recurring utility and service payments

2. Trading Patterns

  • Arbitrage: Cross-exchange trading patterns
  • Market Making: Liquidity provision patterns
  • High-Frequency Trading: Rapid transaction sequences

3. Security Patterns

  • Money Laundering: Suspicious transaction structuring
  • Mixer Usage: Privacy tool usage patterns
  • Exchange Patterns: Centralized exchange interactions

Implementation

Configuration

[pattern_recognition]
enabled = true
model_type = "ensemble"
update_interval = "1h"
min_confidence = 0.8

[pattern_recognition.features]
temporal = true
amount = true
address_clustering = true
network_analysis = true

API Usage

use anya_enterprise::analytics::PatternRecognizer;

let recognizer = PatternRecognizer::new(config).await?;
let patterns = recognizer.analyze_transactions(&transactions).await?;

for pattern in patterns {
    println!("Found pattern: {:?} (confidence: {:.2})", 
             pattern.pattern_type, pattern.confidence);
}

Performance Metrics

Pattern Type Detection Rate False Positive Rate Processing Time
Payment Schedules 95% 2% 50ms
Trading Patterns 88% 5% 120ms
Security Patterns 92% 1% 200ms

See Also

For more information, see the Advanced Analytics overview.