Article Review #2
Understanding the Use of Artificial Intelligence in Cybercrime
Matthew Burd
3/20/25
Understanding the Intersection of AI and Cybercrime
Introduction – (BLUFF Heading)
The growing role of artificial intelligence (AI) in enabling cybercrime is examined in the article, “Understanding the Use of Artificial Intelligence in Cybercrime” by Choi, Dearden, and Parti (2024). The authors highlight how hackers have been able to intensify their illegal activities due to technological improvements, especially artificial intelligence (AI), which has made attacks more complex and challenging to identify. This evaluation discusses research questions and hypotheses, assesses the methodology employed, looks at how the article complies with important social science principles, and highlights the study’s contributions to the field of cybersecurity.
Social Science Principles and Research Framework
This article examines AI-driven cybercrime using three fundamental social science concepts as described in the PowerPoints. Determinism, skepticism, and empiricism. Cybercriminals’ predictable use of AI, including automation, deepfakes, and social engineering, is deterministic (Choi et al., 2024). This is consistent with criminological views that attribute technical opportunities to criminal activity. When evaluating AI’s dual role in cybersecurity, skepticism is essential, and ongoing examination of security protocols is encouraged. The study’s data-driven methodology, which assesses AI-powered cyber threats through case studies and statistical analyses, reflects empiricism. The paper concludes that developing AI necessitates sophisticated security responses after examining how AI promotes cybercrime, new trends, and successful defenses.
Research Methods and Data Analysis
Using a mixed-methods approach, the study combines quantitative and qualitative analysis. The authors look at case examples of cybercrimes that are made possible by AI, including malware that is fueled by AI, phishing emails that are created by AI, and deepfake scams (Shetty et al., 2024). A statistical analysis of cybercrime trends is also included in the paper, which assesses the rising sophistication and frequency of attacks using AI technologies. A thorough examination of the dynamics of cybercrime is made possible by the incorporation of criminological frameworks, such as RAT and Cyber-RAT.
The article’s data analysis shows a distinct trend: AI is growing in strength as a tool for cybercriminals since it can automate extensive attacks and get beyond conventional security measures. To lessen AI-driven cyber threats, the report emphasizes the necessity of enhanced user cyber hygiene, stricter digital guardianship, and legislative measures.
Relevance to Marginalized Groups and Conceptual Linkages
Marginalized groups are disproportionately impacted by AI-enhanced crimes, especially those with less access to cybersecurity services and digital literacy. The study highlights how people from low-income backgrounds are especially vulnerable to financial fraud and scams powered by artificial intelligence. Additionally, because of behavioral vulnerabilities, AI-based social engineering attacks often target women and elderly persons.
The subject is related to several ideas from criminology and cybersecurity courses, such as digital forensics, cyber risk management, and the psychological manipulation techniques employed in social engineering. By connecting these ideas to AI-driven cybercrime, the study emphasizes the necessity of a multidisciplinary approach to addressing cybersecurity risks.
Contributions and Conclusion
Two significant additions to the field of cybersecurity are made by the study. First, it offers a thorough examination of how artificial intelligence is changing cybercrime, providing insightful information for security experts, legislators, and law enforcement. Second, to explain cybercrime activities, it suggests an innovative theoretical structure called the Integrated Model of Cybercrime Dynamics (IMCD), which integrates environmental variables, individual behaviors, and AI-driven tools (Smith, 2024).
In conclusion, Choi et al. (2024) offer a convincing examination of AI’s increasing role in cybercrime, showcasing how it might improve the intricacy and potency of cyberattacks. According to the study, to reduce AI-driven dangers, there is an urgent need for interdisciplinary cooperation, improved cybersecurity, and well-informed legislation. The results of this work provide an essential basis for future research and policy creation, as hackers persist in using AI for malicious intent.
References
Choi, S., Dearden, T., & Parti, K. (2024). Understanding the Use of Artificial Intelligence in Cybercrime. International Journal of Cybersecurity Intelligence & Cybercrime, 7(2). https://doi.org/10.52306/2578-3289.1185
Shetty, S., Choi, K., & Park, I. (2024). Investigating the Intersection of AI and Cybercrime: Risks, Trends, and Countermeasures. International Journal of Cybersecurity Intelligence and Cybercrime, 7(2), 28-53.
Smith, T. (2024). Integrated Model of Cybercrime Dynamics: A Comprehensive Framework for Understanding Offending and Victimization in the Digital Realm. International Journal of Cybersecurity Intelligence and Cybercrime, 7(2), 54-70.