Criminal clickbait: a panel data analysis on the attractiveness of online advertisements offering stolen data - Madarie, Renushka; de Poot, Christianne; Weulen Kranenbarg, Marleen (Frontiers in Big Data, 2023)
Few studies have examined the sales of stolen account credentials on darkweb markets. In this study, we tested how advertisement characteristics affect the popularity of illicit online advertisements offering account credentials. Unlike previous criminological research, we take a novel approach by assessing the applicability of knowledge on regular consumer behaviour instead of theories explaining offender behaviour. We analyse a large panel data set containing 1,565 unique advertisements to predict the simultaneous effects of the asking price, endorsement cues and title elements on advertisement popularity. Surprisingly, most of our findings disconfirm our hypotheses. Asking price did not affect advertisement popularity. Vendor reputation and cumulative sales and views had mixed and negative relationships respectively with ad popularity. These results could suggest that account credentials are not simply regular products, but high-risk commodities that, paradoxically, become less attractive as they gain popularity. Our study reveals that conventional consumer behaviour expectations do not fully apply in this context. This highlights the necessity of a deeper understanding of illicit online market dynamics to improve theories on illicit consumer behaviours and assist cybersecurity experts in disrupting criminal business models more effectively. We propose several avenues for future experimental research to gain further insights into these illicit processes.