Quantum Key Distribution

for Razorpay Security

Enhancing Payment Security with Quantum Cryptography

Combining BB84 Protocol with AI-Powered Fraud Detection

QKD Research Team
March 2025
Quantum Cryptography Lab

Problem Statement

Current payment systems face unprecedented challenges in the quantum era

Current Challenges

  • Increasing sophistication of payment fraud attacks
  • Quantum computers threaten traditional encryption
  • Need for real-time fraud detection systems
  • Balancing security with user experience

Rising payment fraud cases (2019-2023)

Our Solution

  • Implement BB84 quantum key distribution protocol
  • Develop neural network-based fraud detection
  • Integrate with Razorpay payment infrastructure
  • Create real-time monitoring dashboard

Integrated QKD solution approach

BB84 Quantum Protocol

The foundation of quantum-secure key distribution

BB84 Protocol

Key Advantage

Physically impossible to copy unknown quantum states without detection - guaranteed by laws of physics

Protocol Steps

1

Qubit Preparation

Alice encodes random bits in two quantum bases (rectilinear and diagonal)

2

Quantum Transmission

Qubits are transmitted through quantum channel to Bob

3

Random Measurement

Bob measures qubits in randomly chosen bases

4

Basis Reconciliation

Alice and Bob compare basis choices over classical channel

5

Eavesdropping Detection

Error rate analysis reveals any interception attempts

6

Privacy Amplification

Final secure key generation with enhanced security

System Architecture

Integrated quantum-secured payment processing system

System Architecture

Our integrated system provides end-to-end quantum-secured payment processing

QKD Module

Generates unbreakable encryption keys using quantum principles

  • BB84 protocol implementation
  • Error correction algorithms
  • Privacy amplification

Encryption Layer

Secures all payment data with quantum-derived keys

  • AES-256 encryption
  • Secure key rotation
  • Forward secrecy

Fraud Detection

Neural network analysis for real-time threat identification

  • Anomaly detection
  • Transaction pattern analysis
  • Behavioral biometrics

Razorpay API

Seamless integration with payment processing infrastructure

  • Secure API endpoints
  • Transaction lifecycle management
  • Compliance mechanisms

QKD Performance Results

Our tests demonstrate a 72-96% eavesdropper detection rate under various conditions
QKD Visualization

Real-time QKD visualization showing qubit transmission

Key Insights

Eavesdropper presence significantly drops success rate to 28-64%

Higher error rates (0.05) improve eavesdropper detection

Processing time remains efficient (< 2s) even with security checks

Quantum security automatically blocks compromised payments

Performance Data

Qubits Error Rate Eavesdropper Success Rate Avg. Time (s)
500 0.01 No 98% 0.87
1000 0.01 No 97% 1.52
1000 0.05 No 92% 1.54
1000 0.01 Yes 64% 1.67
1000 0.05 Yes 28% 1.71

Neural Network Fraud Detection

Advanced AI-powered fraud detection using deep learning

Neural Network Architecture

Technical Specifications

Framework
TensorFlow 2.7
Training
50 epochs, batch 64
Optimizer
Adam (lr=0.001)
Loss Function
Binary Cross-Entropy

Network Architecture

Layer Neurons Activation Purpose
Input 16 - Feature ingestion
Hidden 1 128 ReLU Feature extraction
Hidden 2 64 ReLU Pattern recognition
Hidden 3 32 Tanh Non-linear mapping
Output 1 Sigmoid Fraud probability

Advantages of Our Approach

Learns complex patterns impossible for rule-based systems

Adapts to evolving fraud techniques

Reduced false positives compared to traditional methods

Complements quantum security for defense-in-depth

Fraud Detection Performance

Comprehensive analysis of our neural network's fraud detection capabilities

95.8%
Accuracy
Overall classification correctness
41.2%
Precision
Correct fraud predictions
13.4%
Recall
Fraud cases identified
20.2%
F1 Score
Harmonic mean
73.2%
AUC
ROC curve area
Confusion Matrix

Confusion Matrix: Most legitimate transactions correctly classified

Loss Curves

Loss Curves: Model convergence without overfitting

Accuracy Curves

Accuracy Curves: Consistent improvement during training

Key Finding

Our model achieves high accuracy (95.8%) in an imbalanced dataset where fraud transactions are rare. The quantum-neural hybrid approach provides exceptional protection against both traditional and quantum threats.

System Implementation

Technical architecture and implementation details

System Design

Sequence Diagram

Transaction flow sequence

Class Diagram

System component architecture

Core Technologies

Python 3.8+
Qiskit
AES-GCM
JavaScript
Flask
TensorFlow

Integration Approach

Data Flow Diagram

Data flow between system components

Future Research Directions

Exploring the next frontier of quantum-secured financial systems

Hardware Integration

Develop FPGA-based QKD hardware for dedicated key generation

Custom quantum circuitry for improved performance

Tamper-resistant hardware security modules

Miniaturization for broader deployment scenarios

Satellite QKD

Partner with space agencies to implement satellite-based QKD

Extend secure communication to global scale

Overcome distance limitations of fiber-based QKD

Create quantum secure global financial network

Quantum Internet

Integrate with emerging quantum internet standards

Implement quantum repeaters for extended reach

Develop quantum routers for key distribution

Create end-to-end quantum-secured connections

Post-Quantum Security

Combine QKD with post-quantum cryptographic algorithms

Hybrid security approach for defense in depth

Lattice-based and hash-based signature schemes

Quantum-resistant wallets and payment tokens

Research Roadmap

Project Initiation

Simulation-based QKD for Razorpay

1
Phase 1
Phase 2
2

Field Testing

Physical QKD implementation with select merchants

API Platform

Open QKD-as-a-Service for fintech applications

3
Phase 3
Phase 4
4

Global Network

Quantum-secured payment network across continents

Quantum-Secure the Future

Join Our Quantum Security Initiative

By integrating quantum technology with traditional payment systems, we've created a security framework that's prepared for tomorrow's quantum threats.

Provable security guarantees based on quantum physics

Enhanced fraud detection using neural networks

Seamless integration with existing payment infrastructure

Future-proof against quantum computing threats

Get In Touch

krrishchoudhary109@gmail.com
+91 7877624097