Exposing the Impact of GenAI for Cybercrime: An Investigation into the Dark Side
It addresses the dual-use risks of generative AI for cybersecurity, providing data to inform policymakers, developers, and the public, though it is incremental in building on known concerns.
This paper investigates the link between generative AI and cybercrime, finding empirical evidence that it amplifies malicious internet activities, with analysis of general and cryptocurrency datasets showing significant increases in such activities.
In recent years, the rapid advancement and democratization of generative AI models have sparked significant debate over safety, ethical risks, and dual-use concerns, particularly in the context of cybersecurity. While anecdotally known, this paper provides empirical evidence regarding generative AI's association with malicious internet-related activities and cybercrime by examining the phenomenon through psychological frameworks of technological amplification and affordance theory. Using a quasi-experimental design with interrupted time series analysis, we analyze two datasets, one general and one cryptocurrency-focused, to empirically assess generative AI's role in cybercrime. The findings contribute to ongoing discussions about AI governance by balancing control and fostering innovation, underscoring the need for strategies to guide policymakers, inform AI developers and cybersecurity professionals, and educate the public to maximize AI's benefits while mitigating its risks.