The responsiveness of criminal networks to intentional attacks: Disrupting darknet drug trade

Abstract

Physical, technological, and social networks are often at risk of intentional attack. Despite the wide-spanning importance of network vulnerability, very little is known about how criminal networks respond to attacks or whether intentional attacks affect criminal activity in the long-run. To assess criminal network responsiveness, we designed an empirically-grounded agent-based simulation using population-level network data on 16,847 illicit drug exchanges between 7,295 users of an active darknet drug market and statistical methods for simulation analysis. We consider three attack strategies: targeted attacks that delete structurally integral vertices, weak link attacks that delete large numbers of weakly connected vertices, and signal attacks that saturate the network with noisy signals. Results reveal that, while targeted attacks are effective when conducted at a large-scale, weak link and signal attacks deter more potential drug transactions and buyers when only a small portion of the network is attacked. We also find that intentional attacks affect network behavior. When networks are attacked, actors grow more cautious about forging ties, connecting less frequently and only to trustworthy alters. Operating in tandem, these two processes undermine long-term network robustness and increase network vulnerability to future attacks.

A Depiction and Classification of the Stolen Data Market Ecosystem and Comprising Darknet Markets: A Multidisciplinary Approach

“…Targeted intervention efforts have already proven effective at reducing the frequency and severity of cybercrime incidents (Maimon et al, 2021). Large-scale attacks on the darknet ecosystem, for example, create distrust (Duxbury & Haynie, 2020) and lead to a reduction in the number of active vendors selling products (Chan et al, 2019). As such, viewing darknet markets as an interconnected network, and targeting markets that comprise a large portion of the ecosystem, should maximize the disruption effect of existent cybercrime intervention strategies.…”

Understanding markers of trust within the online stolen data market: An examination of vendors’ signaling behaviors relative to product price point

“…4 Choice paralysis is based on the idea that having an overabundance of options can cause individuals to complicate decision-making, resulting in higher levels of anxiety, indecision, and dissatisfaction (see Schwartz, 2014). 5 Identifying dependable measures of trust within the online illicit marketplace is inherently challenging since criminal network data are usually incomplete, thus requiring researchers to assume that the observed network is an adequate representation of the unmeasured criminal network (see Duxbury & Haynie, 2020). In the absence of complete trade records and transaction histories, extant research has relied on various metrics of criminal interaction that indirectly measure the mechanics of criminal behavior (Diviak er al., 2019;Papachristos & Smith, 2013).…”

“…Understanding the relationship between vendors' signaling behaviors and trust is important as it could assist law enforcement devise effective intervention strategies targeted at disrupting the online illicit marketplace (see Duxbury & Haynie, 2020;Holt et al, 2013). For instance, identifying the signaling mechanisms that convey trust in the online underground marketplace could help undercover law enforcement agents disguise themselves as credible sellers to both take down and apprehend serious market actors (see Jacobs, 1996aJacobs, , 1996b.…”

“…Though online stolen data markets represent crimes that involve the sale of private data acquired through somewhat sophisticated methods (e.g., malware infection, social engineering), research suggests these behaviors may be committed by individuals who are motivated by similar human decision‐making processes as traditional illicit market crimes (see Duxbury & Haynie, 2020; Grabosky, 2006; Leukfeldt & Holt, 2019). Rational choice theory is particularly valuable to the study of illicit markets and their operational practices, as it assumes actors make calculated decisions as to which markets, vendors, and products are sought out to maximize pleasure and minimize risk (see Becker, 1968; Clarke, 1997).…”

Themes in data mining, big data, and crime analytics

“…The dark net (or dark web) is commonly used for illegal sales (drugs, weapons), organized crime offenses and money laundering or other economic crime offense (Bancroft, 2020). Duxbury and Haynie (2020) used SNA techniques on 16,847 illicit drug exchanges between 7295 users of an active dark net drug market to test for network robustness and vulnerability. They found that when networks are attacked, actors grow more cautious about forging ties, connecting less frequently and only to trustworthy alters.…”