A Data Analytics Strategy to the Underground Economy of Cybercrime

Varun, P.R. and Usha, Sree and Malathy, Batumalay (2024) A Data Analytics Strategy to the Underground Economy of Cybercrime. Journal of Data Science, 2024 (12). pp. 1-7. ISSN 2805-5160

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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.

Item Type:	Article
Uncontrolled Keywords:	CAAS, Cyberattacks, classification, ransomware
Subjects:	Q Science > Q Science (General) Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software
Depositing User:	Unnamed user with email masilah.mansor@newinti.edu.my
Date Deposited:	24 Jun 2024 05:51
Last Modified:	30 Jun 2024 08:49
URI:	http://eprints.intimal.edu.my/id/eprint/1928

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