The dark web is host to hundreds of counterfeit markets the plan doesn’t solve for

Counterfeits harm consumers, governments, and intellectual property holders. They accounted for 3.3% of worldwide trades in 2016, having an estimated value of $509 billion in the same year. Estimations in the literature are mostly based on border seizures, but in this paper, we examined openly labeled counterfeits on darknet markets, which allowed us to gather and analyze information from a different perspective. Here, we analyzed data from 11 darknet markets for the period Jan-2014 and Sep-2015. The findings suggest that darknet markets harbor similar counterfeit product types to those found in seizures but that the share of watches is higher while the share of electronics, clothes, shoes, and Tobacco is lower on darknet markets. Also, darknet market counterfeits seem to have similar shipping origins as seized goods, with some exceptions, such as a relatively high share (5%) of dark market counterfeits originating from the US. Lastly, counterfeits on dark markets tend to have a relatively low price and sales volume. However, based on preliminary estimations, the equivalent products on the surface web appear to be advertised for a multiple of the prices found for darknet markets. We provide some suggestions on how information about darknet market counterfeits could be used by companies and authorities for preventative purposes, showing that insight gathering from the dark web is valuable and could be a cost-effective alternative (or compliment) to border seizures. Thus, monitoring darknet markets can help us understand the counterfeit landscape better.

Introduction Counterfeits are illicit goods that violate intellectual property (IP) rights such as copyrights, trademarks, design rights, or patents, and they can exist physically or digitally (OECD/EUIPO, 2019; WTO, 1994). The purpose of a deceptive counterfeit is to make a monetary profit by deceiving a customer that the product is of a higher value than it is (e.g., by selling it as being genuine) (OECD/EUIPO, 2019). Deceptive counterfeits can be sold directly to consumers or mixed within supply chains of genuine products to reduce costs and increase profits (Hollis & Wilson, 2014). Counterfeits can cause a variety of problems, such as physical (e.g., through foods or pharmaceuticals) and monetary harms to the consumer, the IP holder (e.g., through damages to the brand value, loss of sales), or the government (e.g., through the loss of tax income) (EMCDDA-Europol, 2017; OECD/EUIPO, 2019). In turn, the sales of counterfeits can support organized crime groups financially and facilitate other illegal activities, such as money laundering (EMCDDA-Europol, 2017; UNICRI & ICC BASCAP, 2013; UNODC, 2014). OECD/EUIPO (2019) estimated that counterfeits made up 3.3% of worldwide trades in 2016, worth USD 509 billion. Furthermore, the proportion of counterfeits seems to be elevated within developed regions, such as the European Union (EU). However, estimating counterfeit goods' trade (value) is difficult and is mostly achieved through auditing goods seized at borders (OECD, 2018; OECD/EUIPO, 2019). Thus, current estimates often exclude domestically traded counterfeits or digital products, and since not all counterfeits will be seized at ports, estimates of what is traded may be incomplete. For example, the number of routinely checked containers at major ports in Genoa (Italy), Melbourne (Australia), Montreal (Canada), New York (USA), and Liverpool (UK) together only account for 2–5% of all traffic (Sergi, 2022). Since only a limited number of containers can be checked, the selection procedure can strongly impact possible finds. A theoretical and empirical understanding of how counterfeiting occurs is currently not well developed, perhaps due to the complex involvement of various stakeholders, which results in difficulties for researchers to obtain reliable data (Sullivan et al., 2017). For example, many companies affected by counterfeiting operate across nations, affecting the ease with which authorities can monitor and combat counterfeits. Moreover, the definition of counterfeits varies across nations, further complicating how counterfeiting is measured. However, theories provide perspectives as to why counterfeiting occurs and how it might be addressed. The Rational Choice perspective considers the offender's choice to commit a crime (e.g., counterfeiting a product) and influencing factors of the offenders' decisions, such as the perceived risks and rewards (Clarke & Cornish, 1985). The perspective informs us that while changing the perceived risks and rewards of the offender, the likelihood of offending can be altered and reduced, for example, by increasing the perceived risks of detection or by increasing the general efforts needed to commit a crime. Within the context of counterfeits facilitating the traceability of genuine products within a supply chain (e.g., through watermarks) seems to be a possible approach to increasing the efforts to counterfeit (Gayialis et al., 2022). Another perspective, such as the Routine Activity Approach (RAA), discussed by Spink et al., (2013, 2014), states that crime is more likely when a suitable target (e.g., a product that can be counterfeited) and a motivated offender converge absent a capable guardian (Cohen & Felson, 1979). Capable guardians can include those involved in security at country borders or those involved in inspecting goods at other stages of the supply chain (Marucheck et al., 2011; Tang, 2006). For example, when manufactured products are transported, transport personnel and employees could also act as guardians (Hollis & Wilson, 2014). However, effective guardianship requires a clear understanding of the problem and processes to monitor it, such as reporting procedures. Absent this understanding, guardianship will be less effective. With this in mind, risk assessments are often conducted to aid decisions made by authorities at borders based on intelligence from federal and local authorities and custom officer experiences (Sergi, 2022). However, these are likely to be imperfect. Furthermore, border checks can be random or may only be informed by the country of origin, or how the delivery is labeled, as in the case of parcel shipments (Männistö et al., 2021). Another source of possible bias present in check-selection procedures are large differences in the estimates of counterfeit product types produced by different agencies (IP Crime Group, 2015; OECD/EUIPO, 2019). For example, estimates strongly differ across agencies for footwear (20 percentage points) or for electronics (11%) and clothing (10%). For other products, estimations may be missing entirely, as in the case of Tobacco, which was estimated to make up 28% of all counterfeits by the IP Crime Group (2015) but was not identified as a counterfeited product by OECD/EUIPO (2019). Since different agencies use different data sources (e.g., border or inland seizures), some measurement differences are to be expected, but they also illustrate how inconsistently seizures reflect the true prevalence of counterfeits. Thus, additional data sources to estimate counterfeit affected products would be helpful to better understand the counterfeit landscape and aid efforts at prevention.

With the emergence of dark markets which do not have formal guardians in the same way that open web platforms do, new ways of trading illicit goods, including counterfeits, have appeared (Christin, 2013; van Wegberg et al., 2018), which may serve as an additional data source to measure counterfeit prevalence. Dark markets are online shopping platforms on the deep web—a highly anonymized part of the internet that is not indexed by traditional search engines—which operate like their surface web counterparts, eBay or Amazon. Vendors on dark markets offer a range of illegal products and services, mainly consisting of drugs, but also including hacking services, weapons, guides on how to defraud people, and counterfeits (Baravalle & Lee, 2018; Roberts & Hernandez-Castro, 2017; Soska & Christin, 2015; van Wegberg et al., 2018). During the COVID-19 pandemic, dark markets also started to offer a mix of genuine and fake protective gear (masks, gloves, etc.), medicines, and COVID-19 vaccines (Bracci et al., 2021a, 2021b; Broadhurst & Ball, 2020). Even with successful disruptions and the closing of markets by law enforcement, dark markets increasingly trade in such products and services (Décary-Hétu & Giommoni, 2017; ElBahrawy et al., 2020; EMCDDA-Europol, 2017). On dark markets, vendors openly sell counterfeits and forgeries, which provides an interesting opportunity to gain insight into the counterfeit market from a new angle. Since some dark markets also register the number of goods sold and buyers leave reviews, we can use such information to generate estimates of sales volumes and the monetary value of counterfeits over time. By comparing counterfeit listings and their sales on dark markets to border seizures, we can also see if they differ and provide a more comprehensive picture, which would be of value to law enforcement, companies that are affected by counterfeits of their products, and policymakers.

Therefore, to better understand the counterfeit economy on the dark web, we examined the prevalence and sales of counterfeits sold on 89 dark markets for the 3-year period January 2014–January 2017. Specifically, we quantified the price, volume, type, and origins of advertised counterfeits and estimated their sales volume and the value the same counterfeits would attract on the surface web. We then compare the results to measures and estimations from border seizures conducted by law enforcement over the same period. By highlighting differences, we can identify product groups for which counterfeiting appears to be a problem and would be overlooked based on an analysis of seizures alone. Fraud and counterfeits on dark markets

Studies that have investigated the types of products listed and sold on the dark web mostly cover illegal drugs, which often account for 60–80% of all listings on a dark market (Baravalle & Lee, 2018; EMCDDA-Europol, 2017). However, some studies have examined less frequently listed products, such as art, wildlife, and plane tickets (Hutchings, 2018; Paul, 2018; Roberts & Hernandez-Castro, 2017). Others focus on fraud-related products or services, such as credit card information, online accounts (e.g., e-bay), social engineering guides and tutorials, or financial malware (e.g., ransomware) (Garg et al., 2015; Marin et al., 2016; Schafer et al., 2019; van Wegberg et al., 2018). Although some of these studies have considered the sale of forged documents (e.g., passports, licenses, diplomas), none have investigated or quantified the sales of counterfeits in a systematic way, such as differentiating between clothing, shoes, electronics, or jewelry; product types which can also be found on surface web markets (e.g., eBay, Amazon). Europol (2017) draws attention to IP crime on the dark web and estimates that solely counterfeit goods make up around 1.5–2.5% of all listings on such markets. The report lists some of the types of counterfeits sold on darknet markets (e.g., clothes, accessories, electronics, jewelry, pirated goods), and discusses the presence of wholesalers, which seem to account for the minority of transactions but most of the sales volume. In contrast, they report that most of the transactions are through the sales of individual items but seem to account for the minority of sales volume. According to this report, counterfeits seem to be sold for 1/3 of the price of the equivalent genuine product, and digital goods for around 1/6 of their original price (Europol, 2017). The report concludes that while the sale of IP goods is limited, there is potential for growth on darknet markets, and IP goods on dark markets should be monitored and investigated in more detail. However, the report does not explain how the mentioned statics were obtained nor which darknet markets were included in the analyses, making it difficult to assess the extent of counterfeits on the dark web. Furthermore, the lack of granularity prevents us from understanding which product types are offered, how frequently, how much they are sold, and where they originate. Lastly, the Europol (2017) report does not differentiate between counterfeits that could be sold on the surface web (e.g., shoes, clothes, electronics) and counterfeits that are limited to the dark web (e.g., fake banknotes or IDs), which is important if we want to inform authorities or companies on potentially affected product types that could be sold on the surface web.