Threat Detection Latency ANOVA

import matplotlib.pyplot as plt
import numpy as np
import scipy.stats as stats

np.random.seed(321)

# Detection latency in milliseconds
legacy_ids = np.random.exponential(450, 150) + 200
ml_based = np.random.exponential(80, 150) + 50
ai_siem = np.random.exponential(25, 150) + 15

# Clip extreme values for visualization
legacy_ids = np.clip(legacy_ids, 0, 2000)
ml_based = np.clip(ml_based, 0, 500)
ai_siem = np.clip(ai_siem, 0, 150)

F_stat, p_value = stats.f_oneway(legacy_ids, ml_based, ai_siem)

fig, ax = plt.subplots(figsize=(11, 7), facecolor='#0a0a0f')
ax.set_facecolor('#0a0a0f')

colors = ['#C82909', '#F5B027', '#6CF527']

parts = ax.violinplot([legacy_ids, ml_based, ai_siem], 
                       positions=[1, 2, 3], showmeans=True, showmedians=True, widths=0.75)

for i, pc in enumerate(parts['bodies']):
    pc.set_facecolor(colors[i])
    pc.set_alpha(0.7)
    pc.set_edgecolor(colors[i])
    pc.set_linewidth(2)

parts['cmeans'].set_color('#27D3F5')
parts['cmeans'].set_linewidth(2.5)
parts['cmedians'].set_color('white')
for partname in ['cbars', 'cmins', 'cmaxes']:
    parts[partname].set_color('#444444')

# Detection rate annotations at bottom
detection_rates = [92.3, 97.8, 99.6]
labels = ['Legacy IDS', 'ML-Based', 'AI-SIEM']
for i, (rate, color) in enumerate(zip(detection_rates, colors)):
    ax.text(i+1, -150, f'Detection: {rate}%', ha='center', fontsize=9, 
            color=color, fontweight='bold')

# Threat level indicator
ax.axhline(y=100, color='#F5276C', linestyle='--', alpha=0.7, linewidth=1.5)
ax.text(3.35, 100, 'Critical', fontsize=9, color='#F5276C', va='center')

# Stats box - compact at top
stats_text = f"ANOVA: F={F_stat:.1f}, p<0.001"
bbox = dict(boxstyle="round,pad=0.3", facecolor='#020B14', edgecolor='#6CF527', lw=2)
ax.text(0.5, 1.02, stats_text, transform=ax.transAxes, fontsize=10, color='#6CF527',
        ha='center', va='bottom', fontfamily='monospace', bbox=bbox)

ax.set_xticks([1, 2, 3])
ax.set_xticklabels(labels, fontsize=12, color='white')
ax.set_ylabel('Detection Latency (ms)', fontsize=12, color='white', fontweight='500')
ax.set_title('Intrusion Detection System Performance\nThreat Response Time Comparison', 
             fontsize=14, color='white', fontweight='bold', pad=25)

ax.tick_params(colors='#888888')
for spine in ax.spines.values():
    spine.set_color('#333333')
ax.yaxis.grid(True, color='#1a1a2e', linewidth=0.5)
ax.set_axisbelow(True)
ax.set_ylim(-200, 2100)

plt.tight_layout()
plt.show()