The growth of cybercrime

Python

import pandas as pd  import matplotlib.pyplot as plt    # Data compiled from search results  data = {      'Year': [2015, 2021, 2023, 2025],      'Cybercrime Economy': [3.0, 6.0, 8.0, 10.5],      'USA GDP': [18.295, 23.681, 27.721, 30.507],      'China GDP': [11.281, 18.202, 17.795, 19.232]  }    df = pd.DataFrame(data)    # Set the Year as the index for easier plotting  df = df.set_index('Year')    # Create the plot  plt.figure(figsize=(10, 6))    # Plot the three series  df['USA GDP'].plot(kind='line', marker='o', label='USA GDP', color='blue')  df['China GDP'].plot(kind='line', marker='o', label='China GDP', color='red')  df['Cybercrime Economy'].plot(kind='line', marker='o', label='Global Cybercrime Economy', color='black')    # Add titles and labels  plt.title('Growth Comparison: Global Cybercrime Economy vs. USA and China GDP', fontsize=14)  plt.xlabel('Year', fontsize=12)  plt.ylabel('Economic Value (Trillion USD)', fontsize=12)    # Add a legend  plt.legend(title='Economic Entity')    # Add grid lines for better readability  plt.grid(True, linestyle='--', alpha=0.6)    # Add annotations for the 2025 forecast  for year in [2025]:      plt.annotate(          f"USA: ${df.loc[year, 'USA GDP']:.1f}T (F)",          (year, df.loc[year, 'USA GDP']),          textcoords="offset points",          xytext=(-30,-20),          ha='center',          fontsize=9,          color='blue'      )      plt.annotate(          f"China: ${df.loc[year, 'China GDP']:.1f}T (F)",          (year, df.loc[year, 'China GDP']),          textcoords="offset points",          xytext=(30,-20),          ha='center',          fontsize=9,          color='red'      )      plt.annotate(          f"Cybercrime: ${df.loc[year, 'Cybercrime Economy']:.1f}T (F)",          (year, df.loc[year, 'Cybercrime Economy']),          textcoords="offset points",          xytext=(0,10),          ha='center',          fontsize=9,          color='black'      )  plt.xticks(df.index)    # Save the figure  plt.savefig('economic_growth_comparison_cybercrime.png')    print("economic_growth_comparison_cybercrime.png")    

Code output

economic_growth_comparison_cybercrime.png    

The graph compares the nominal Gross Domestic Product (GDP) of the USA and China with the estimated annual Global Cybercrime Economy (in Trillions of USD) forecast from 2015 to 2025.

The data clearly illustrates the alarming rate of growth of the dark digital economy.

Key Observations from the Graph:

• Rapid Growth: The Global Cybercrime Economy is projected to more than triple in just one decade, growing from $3.0 trillion in 2015 to an estimated $10.5 trillion by 2025. Cybersecurity Ventures estimates that global cybercrime will cost $10.5 trillion annually by 2025, making it the world's third-largest economy after the U.S. and China.

• The "Third Economy": By 2025, the annual cost of global cybercrime is forecasted to exceed the GDP of every nation except the United States and China, solidifying its status as the world's "third-largest economy."

• Scale of the Threat: Although still smaller in absolute size than the two largest national economies, the rapid growth of the cybercrime economy represents a massive and expanding transfer of wealth, draining resources from both public and private sectors worldwide.

Year	Global Cybercrime Cost (Trillion USD)	USA GDP (Trillion USD)	China GDP (Trillion USD)
2015	$3.0	$18.3	$11.3
2021	$6.0	$23.7	$18.2
2025 (F)	$10.5	$30.5	$19.2

The data confirms that the global challenges in securing digital assets are increasing exponentially, underscoring the need for fundamentally safer computing paradigms, such as the capability-based development as the PP250 microcode.