Project Name
CKB Wallet Behaviour Intelligence
Team
- GitHub: FadhilMulinya
- Role: Product engineer with experience building blockchain infrastructure, indexing systems, backend services, and developer tooling
- Telegram: mulinyaaa
- Email: [email protected]
Project Description
Problem
CKB provides transparent and rich on-chain data through its Cell-based architecture, but there is currently no open-source tooling that converts raw transaction data into actionable behavioral intelligence.
Developers can easily access transaction histories through explorers and APIs, but understanding how a wallet behaves still requires significant custom analysis and infrastructure.
Questions such as:
- Is this wallet behaving like an individual user?
- Does this wallet exhibit highly automated activity?
- Is this wallet likely operating as an exchange-controlled wallet?
- Does this wallet demonstrate unusual transaction behavior compared to typical network participants?
cannot currently be answered through a simple API or reusable ecosystem tool.
As the CKB ecosystem grows, analytics platforms, wallet providers, security tooling, explorers, and future infrastructure services can benefit from richer wallet context rather than relying solely on raw transaction records.
This project is not focused on detecting low-cost Sybil attacks. CKB’s Cell model and state occupation costs already increase the cost of mass wallet creation. Instead, the project focuses on behavioral analysis and wallet classification, providing ecosystem developers with reusable analytics infrastructure built specifically for CKB.
Solution
We propose an open wallet behaviour dataset, feature extraction framework, and baseline classification API for the CKB ecosystem..
The system will analyze wallet transaction histories using machine learning and behavioral feature extraction.
The initial version will focus on:
- Transaction timing patterns
- Transaction frequency patterns
- Wallet interaction graph relationships
- Cell usage and transaction flow characteristics
Using these features, the system will generate:
- Human-like behavior score
- Automated behavior score
- Exchange-like behavior score
- Confidence metrics
Developers will be able to submit a CKB wallet address through an API and receive a behavioral classification result.
The goal of this Spark Program project is to deliver a working prototype that demonstrates how behavioral analytics can enrich wallet intelligence across the CKB ecosystem.
Expected Deliverables
1. Open Source Repository
A public GitHub repository containing:
- CKB data extraction pipeline
- Feature engineering pipeline
- Model training code
- API implementation
- Deployment instructions
- Technical documentation
2. Wallet Classification API
A public REST API capable of:
- Accepting a CKB wallet address
- Returning wallet classification results
- Returning confidence scores
3. Initial Wallet Dataset
A curated dataset containing approximately:
- 500 human-like wallets
- 500 automated and/or exchange-like wallets
The dataset will be publicly available and serve as one of the first open wallet behaviour datasets built specifically for the CKB ecosystem.
4. Documentation
Documentation covering:
- API usage
- Deployment instructions
- Model methodology
- Feature definitions
- Evaluation results
5. Public Demonstration
- Public API endpoint
- Demonstration video
- Project completion report
6. Formal Analysis Report
A formal report containing:
- Model accuracy metrics
- Precision, Recall and F1 Score
- Confusion Matrix
- Dataset size statistics
- Label distribution statistics
- API verification methods
- Open-source repository links
- Findings and limitations
How To Verify
The project can be verified without requiring code review.
Dataset Verification
Reviewers can:
- Download the published dataset
- Verify dataset size
- Verify label distribution
- Inspect feature definitions
Feature Pipeline Verification
Reviewers can:
- Run the feature extraction pipeline
- Generate behavioural features from CKB wallet data
- Reproduce the dataset generation process
API Verification
Reviewers can:
- Submit a CKB wallet address to the API
- Receive classification results
- Verify model outputs against published documentation
Model Verification
Reviewers can:
- Train the baseline model using the published dataset
- Reproduce evaluation metrics
- Validate reported results
Repository Verification
Community members can:
- Access the public GitHub repository
- Review documentation
- Reproduce data extraction and training workflows
Analysis Report Verification
Reviewers can verify:
- Accuracy
- Precision
- Recall
- F1 Score
- Confusion Matrix
- Dataset statistics
through the published report and repository artifacts..
Example integration: A Randomn wallet Provider
**
Required Funding
Developer Time
| Phase | Hours | Description |
|---|---|---|
| Data extraction and feature engineering | 30 hrs | CKB-CCC integration, Explorer API integration, transaction ingestion pipeline, feature engineering |
| Model development and evaluation | 30 hrs | Dataset preparation, model training, model evaluation, classification pipeline |
| API implementation | 25 hrs | REST API development, model serving integration |
| Documentation and open-source release | 15 hrs | QA testing, deployment, documentation, demo preparation and final reporting |
| Total Developer Time | 100 hrs | Approximately 4 weeks of development |
Infrastructure & Deployment Costs
| Item | Unit Cost | Quantity | Subtotal (USD) |
|---|---|---|---|
| VPS hosting (API, model inference server) | $12/month | 2 months | $24 |
| Database | $20/month | 2 months | $40 |
| Domain name for public API and demo | ~$12/year | 1 | $12 |
| Infrastructure & Deployment Subtotal | $76 |
These costs support the public deployment of the Wallet Analytics & Classification API, model serving, dataset storage, monitoring, testing, and demonstration infrastructure required for the Spark Program deliverables.
Effective Hourly Rate
| Metric | Value |
|---|---|
| Total developer hours | 100 hrs |
| Developer budget | $700 |
| Effective hourly rate | $7.00/hr |
Total Developer Compensation
| Item | Amount |
|---|---|
| Infrastructure & deployment costs | $76 |
| Dataset preparation & validation | $124 |
| Developer time | $700 |
| Total grant requested | $900 |
The requested funding supports approximately 100 hours of development work covering blockchain integration, wallet data extraction, feature engineering, machine learning implementation, API development, testing, deployment, documentation, and public demonstration delivery.
Estimated Completion Time
4 weeks total
- Weeks 1–3: active development (data pipeline, feature engineering, dataset construction, model training)
- Week 4: documentation, open-source release, and formal reporting
Clear To-Do List
Week 1
- Integrate CKB-CCC
- Integrate Explorer API
- Build transaction ingestion pipeline
Week 2
- Implement feature extraction pipeline
- Create wallet labeling workflow
- Build initial dataset
Week 3
- Complete labeled dataset
- Train classification model
- Evaluate model performance
- Generate benchmark metrics (Accuracy, Precision, Recall, F1 Score, Confusion Matrix)
Week 4
- Publish dataset
- Publish feature extraction pipeline
- Publish model training code
- Publish API code
- Release open-source repository
- Publish technical documentation
- Publish formal analysis report containing:
Accuracy
Precision
Recall
F1 Score
Confusion Matrix
Dataset statistics
Label distribution
Repository links - Publish project completion report
Relevance to the CKB Ecosystem
Meeting Actual Needs in the CKB Ecosystem
The project provides a reusable wallet analytics layer that can benefit:
- Wallet providers
- Blockchain explorers
- Analytics platforms
- Security monitoring tools
- Future infrastructure services
Today, teams that require wallet behavior analysis must build their own infrastructure and classification logic from scratch.
This project provides an open-source foundation that can be reused and extended by ecosystem participants, reducing duplicated effort while encouraging experimentation with behavioral analytics on CKB.
The project also contributes an initial labeled wallet dataset and wallet classification API that can serve as a starting point for future ecosystem tooling.
Utilizing CKB’s Technical Architecture
The project leverages CKB’s transparent transaction model and Cell-based architecture to extract behavioral signals that are difficult to obtain from simple account balances alone.
Using transaction flows, Cell consumption patterns, transaction timing, and wallet interaction relationships, the system demonstrates how machine learning can be applied to CKB-specific data structures to generate useful wallet insights.
Future Work
The current Spark Program scope focuses exclusively on:
- Wallet dataset construction
- Feature extraction pipeline development
- Baseline model training
- Open-source release
Future work, including advanced model finetuning, ecosystem integrations, dashboard expansion, partner onboarding, and larger-scale dataset growth, will be pursued through a future Community Fund DAO proposal after successful completion of the Spark milestone.
This showcases a practical analytics use case built directly on top of CKB’s unique architecture and provides a foundation for future wallet intelligence and ecosystem analytics tools.
