import dash
from dash import dcc, html
import pandas as pd
import numpy as np
from datetime import datetime, timedelta
from sklearn.ensemble import IsolationForest
from sklearn.preprocessing import StandardScaler
import plotly.graph_objs as go
# Initialize the Dash app
app = dash.Dash(__name__)
server = app.server
# Generate mock data
def generate_mock_data(n_samples=100):
current_time = datetime.now()
timestamps = [current_time - timedelta(minutes=i) for i in range(n_samples)]
data = pd.DataFrame({
'timestamp': timestamps,
'network_traffic': np.random.normal(1000, 200, n_samples),
'failed_logins': np.random.poisson(5, n_samples),
'suspicious_ips': np.random.poisson(2, n_samples),
'data_exfiltration': np.random.normal(50, 10, n_samples)
})
return data
# Detect anomalies
def detect_anomalies(df):
isolation_forest = IsolationForest(contamination=0.1, random_state=42)
scaler = StandardScaler()
features = ['network_traffic', 'failed_logins', 'suspicious_ips', 'data_exfiltration']
X = df[features]
X_scaled = scaler.fit_transform(X)
return isolation_forest.fit_predict(X_scaled) == -1
# Generate data and detect anomalies
df = generate_mock_data()
anomalies = detect_anomalies(df)
# Create figures
def create_network_traffic_figure():
fig = go.Figure()
# Normal traffic
fig.add_trace(go.Scatter(
x=df[~anomalies]['timestamp'],
y=df[~anomalies]['network_traffic'],
name='Normal Traffic',
mode='lines',
line=dict(color='blue')
))
# Anomalies
fig.add_trace(go.Scatter(
x=df[anomalies]['timestamp'],
y=df[anomalies]['network_traffic'],
name='Anomalies',
mode='markers',
marker=dict(color='red', size=10)
))
fig.update_layout(
title='Network Traffic with Anomaly Detection',
xaxis_title='Time',
yaxis_title='Network Traffic (bytes)',
template='plotly_white'
)
return fig
# Create metrics
def generate_metrics():
return {
'Total Anomalies': int(sum(anomalies)),
'Average Network Traffic': f"{float(df['network_traffic'].mean()):.2f}",
'Max Failed Logins': int(df['failed_logins'].max()),
}
# Define the app layout
app.layout = html.Div([
html.H1("AI-Enhanced Cybersecurity Dashboard",
style={'textAlign': 'center', 'padding': '20px'}),
# Metrics Section
html.Div([
html.H2("Key Metrics", style={'textAlign': 'center'}),
html.Div([
html.Table(
[html.Tr([html.Th(k), html.Td(v)]) for k, v in generate_metrics().items()],
style={'margin': 'auto', 'border-collapse': 'collapse'}
)
])
], style={'padding': '20px'}),
# Network Traffic Graph
html.Div([
html.H2("Network Traffic Analysis", style={'textAlign': 'center'}),
dcc.Graph(figure=create_network_traffic_figure())
], style={'padding': '20px'})
])
# Add CSS
app.index_string = '''
{%metas%}
Cybersecurity Dashboard
{%favicon%}
{%css%}
{%app_entry%}
'''
if __name__ == '__main__':
app.run_server(debug=True)