$ETH , BTC. SOL
### Design and Implementation of the Stolen Funds Tracking and Analysis Platform
#### 1. Technology Stack Selection
- **Programming Language**: Python
- **Web Framework**: Django
- **Database**: PostgreSQL
- **Data Processing Framework**: Apache Spark
- **Real-time Stream Processing**: Apache Kafka
- **Visualization**: Plotly, Dash
- **Security Framework**: Django REST framework
#### 2. Project Structure
```
blockchain_tracing_platform/
│
├── apps/
│ ├── data_collection/
│ ├── data_processing/
│ ├── transaction_tracking/
│ ├── visualization/
│ └── user_management/
│
├── config/
│ ├── settings.py
│ └── urls.py
│
├── utils/
│ ├── db_utils.py
│ └── analytics_utils.py
│
├── manage.py
└── requirements.txt
```
#### 3. Main Functionality Implementation
**3.1 Data Collection Module**
```python
# apps/data_collection/models.py
from django.db import models
class BlockchainTransaction(models.Model):
transaction_hash = models.CharField(max_length=255, unique=True)
timestamp = models.DateTimeField()
amount = models.DecimalField(max_digits=20, decimal_places=8)
from_address = models.CharField(max_length=255)
to_address = models.CharField(max_length=255)
block_number = models.IntegerField()
blockchain_network = models.CharField(max_length=50)
def __str__(self):
return self.transaction_hash
```
**3.2 Data Analysis Module**
```python
# apps/data_processing/analytics.py
from apps.data_collection.models import BlockchainTransaction
import pandas as pd
from pyspark.sql import SparkSession
spark = SparkSession.builder.appName("BlockchainAnalytics").getOrCreate()
def detect_anomalies(transactions):
df = transactions.toPandas()
anomalies = df[df['amount'] > 1000000] # Placeholder for real anomaly detection logic
return anomalies
```
**3.3 Transaction Tracking Module**
```python
# apps/transaction_tracking/models.py
from django.db import models
from apps.data_collection.models import BlockchainTransaction
class TransactionChain(models.Model):
transaction = models.OneToOneField(BlockchainTransaction, on_delete=models.CASCADE)
previous_transaction = models.ForeignKey('self', on_delete=models.CASCADE, null=True, blank=True)
def __str__(self):
return self.transaction.transaction_hash
```
**3.4 Visualization and Reporting Module**
```python
# apps/visualization/views.py
import plotly.express as px
from django.http import JsonResponse, FileResponse
from apps.data_collection.models import BlockchainTransaction
import pandas as pd
import os
def transaction_chart(request):
transactions = BlockchainTransaction.objects.all()
df = transactions.toPandas()
fig = px.line(df, x='timestamp', y='amount', title='Transaction Volume Over Time')
fig.write_html("transaction_chart.html")
return FileResponse(open('transaction_chart.html', 'rb'))
```
**3.5 User Management and Permission Control**
```python
# apps/user_management/models.py
from django.db import models
from django.contrib.auth.models import AbstractUser
class CustomUser(AbstractUser):
is_investigator = models.BooleanField(default=False)
bio = models.TextField(blank=True, null=True)
location = models.CharField(max_length=100, blank=True, null=True)
age = models.IntegerField(blank=True, null=True)
user_image = models.ImageField(upload_to='images/', blank=True, null=True)
def __str__(self):
return self.username
