Abstract
As cyber threats continue to escalate in both volume and sophistication, organizations face increasing challenges in assessing their exposure to risk and obtaining reliable cyber insurance coverage. This project aims to develop a Blockchain-Powered Cyber Risk Prediction and Insurance Platform that integrates advanced machine learning (ML) techniques with blockchain technology to provide a secure, transparent, and automated system for cyber risk assessment, insurance policy issuance, and claims processing. The platform collects real-time and simulated cyber event data to predict an organization’s risk level, then automatically generates personalized insurance policies and processes claims through smart contracts. Utilizing decentralized storage (IPFS) and immutable blockchain ledgers ensures data transparency, tamper resistance, and efficient trustless interactions among users and insurers. An administrative dashboard provides analytics and operational oversight, making the platform a comprehensive solution for modern cyber risk management and insurance.
Objectives
The main objectives of this project are:
1. User Management: Develop a secure onboarding and authentication system supporting both blockchain wallet-based and traditional email/password registrations. Implement role-based access control to differentiate users (customers) and insurers/admins. Facilitate KYC compliance and detailed user profile management.
2. Risk Monitoring Engine: Collect and analyze simulated and real system logs, login events, and security incidents to generate dynamic risk scores. Use machine learning models to classify risk levels as Low, Medium, or High, providing explainable outputs for transparency.
3. Machine Learning Engine: Design and implement predictive ML models (e.g., Random Forest, Logistic Regression, Neural Networks) trained on historical data and simulated attack traces to estimate an entity’s cyber risk quantitatively on a scale from 0 to 100.
4. Insurance Policy Management: Automatically generate personalized cyber insurance policies and calculate premiums based on assessed risk scores. Store policy details and related documents securely on IPFS and register hashes on the blockchain for tamper-proof tracking.
5. Admin Dashboard: Build an administrative interface to monitor system-wide user activities, policy statuses, risk distributions, and claims. Include real-time interactive data visualizations using libraries such as Recharts or D3.js to facilitate data-driven decision-making.
• Demo Video
• Complete project
• Full project report
• Source code
• Complete project support by online
• Life time access
• Execution Guidelines
• Immediate (Download)
Hardware Requirements:
Server Infrastructure
High-performance server with multi-core CPUs (e.g., Intel Xeon or AMD EPYC)
RAM: Minimum 64 GB (128 GB recommended for large datasets and ML models)
Storage: SSDs with 2 TB or more for fast data access; additional storage for blockchain nodes
GPU: NVIDIA GPUs (e.g., RTX 3080 or A100) for training ML models efficiently
Network: High-speed internet connection (1 Gbps or higher) for blockchain synchronization and real-time cyber event data
Client Devices
Standard desktops or laptops with web access for administrative dashboards
Optional mobile devices for monitoring via responsive web apps
Software Stack:
Blockchain Layer
Blockchain Framework: Ethereum (for smart contracts) or Hyperledger Fabric (for permissioned blockchain)
Smart Contract Language: Solidity (Ethereum) or Chaincode (Hyperledger)
Decentralized Storage: IPFS for storing logs, insurance policies, and claims securely
Machine Learning & Analytics
Programming Language: Python
Libraries/Frameworks:
ML: scikit-learn, TensorFlow, PyTorch
Data Processing: pandas, NumPy
Visualization: Matplotlib, Seaborn, Plotly
Backend & APIs
Web Framework: Python Flask
Database: Sql lite
Blockchain Integration: Web3.py
Frontend
Framework: HTML CSS, JS
UI Libraries: Material-UI or
Blockchain Development Components:
Solidity (Sol)
Purpose: Programming language for writing smart contracts on Ethereum.
Use in your platform:
Automates insurance policy issuance.
Manages claims processing.
Ensures logic (like payouts based on risk prediction) is transparent and tamper-proof.
Ganache
Purpose: Local blockchain simulator for Ethereum development.
Use in your platform:
Test smart contracts in a safe environment before deploying to the mainnet.
Simulate transactions like policy creation, updates, and claims payouts.
Provides fast iteration for development without incurring real gas fees.
Purpose: Frameworks for compiling, deploying, and testing smart contracts.
Use: Integrates with Ganache and Solidity to automate deployment and testing.
Web3.py
Purpose: Connect frontend/backend to the blockchain.
Use: Your platform can interact with deployed smart contracts to fetch policies, update claims, and verify transactions.
1) Online Order
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