A Data Analytics Strategy to the Underground Economy of Cybercrime

Abstract

Massive cyberattacks and cybercrimes such as ransomware and distributed denial of service
(DDoS) attacks have become more and more of a danger, and individuals, organizations, and
governments have struggled to discover effective means to defend against them. In 2017, the
WannaCry ransomware was to blame for roughly 45,000 strikes across almost 100 nations.
Governments have come under pressure to enhance their cybersecurity spending as a result of
the increasing impact of cybercrime. In his fiscal year 2017 budget, United States President
Barack Obama suggested investing more than $19 billion in cybersecurity, a rise of more than
35% from 2016. Thus, a new sort of organization known as the "cybercrime underground" has
developed, one that both runs underground markets and fosters the growth of cybercrime
conspiracies. The threat posed by the emergence of highly skilled network-based cybercrime
business models, such as Crimeware-as-a-Service (CaaS), is mostly invisible to governments,
organizations, and individuals because cybercrime networks are lateral, diffuse, fluid, and
dynamic. Although cyber dangers are rapidly increasing, there hasn't been much research done
on the methodology or theoretical underpinnings of the field that could help inform information
systems researchers and practitioners who work in the field of cyber security. Additionally, little
is understood about Crime-as-a-Service (CaaS), the illegal business model that supports the
underground world of cybercrime.