key: cord-0545428-4xukvfqy authors: Bracci, Alberto; Nadini, Matthieu; Aliapoulios, Maxwell; McCoy, Damon; Gray, Ian; Teytelboym, Alexander; Gallo, Angela; Baronchelli, Andrea title: The COVID-19 online shadow economy date: 2020-08-04 journal: nan DOI: nan sha: 60f24d34a32b65fcf95054ffbab316252241fa2d doc_id: 545428 cord_uid: 4xukvfqy The COVID-19 pandemic has reshaped the demand for goods and services worldwide. The combination of a public health emergency, economic distress, and disinformation-driven panic have pushed customers and vendors towards the shadow economy. In particular Dark Web Marketplaces (DWMs), commercial websites easily accessible via free software, have gained significant popularity. Here, we analyse 472,372 listings extracted from 23 DWMs between January 1, 2020 and July 7, 2020. We identify 518 listings directly related to COVID-19 products and monitor the temporal evolution of product categories including Personal Protective Equipment (PPE), medicines (e.g., hydroxyclorochine), and medical frauds(e.g., vaccines). Finally, we compare trends in their temporal evolution with variations in public attention, as measured by Twitter posts and Wikipedia page visits. We reveal how the online shadow economy has evolved during the COVID-19 pandemic and highlight the importance of a continuous monitoring of DWMs, especially when real vaccines or cures become available and are potentially in short supply. We anticipate our analysis will be of interest both to researchers and public agencies focused on the protection of public health. DWM trade today is worth at least several hundreds of millions of USD per year, and involves hundreds of thousands of buyers and vendors. [17] [18] [19] [38] [39] [40] As a result, law enforcement agencies have put considerable effort into combating them. 17, 39, 40 Furthermore, DWMs have been targets of cybercriminal actors through use of distributed denial-of-service (DDoS) attacks, hacking attempts, and some even shut down autonomously due to administrators stealing funds from customers directly. 41, 42 However, DWMs have organised into a robust ecosystem which has proven exceptionally resilient to closures and whenever a marketplace is closed, the users trading higher volumes of Bitcoins migrate to active marketplaces or establish new ones. 19 The resiliency and functioning operations of modern DWMs are possible partially because of numerous websites and forums where users can share their experience. One example is Dread, 43 a Reddit-like forum created in 2018 after the closure of the dedicated pages on Reddit. 44 Other ad-hoc platforms exist to monitor whether known marketplaces are active or currently unavailable. [45] [46] [47] [48] Other mechanisms to enhance the resilience of these marketplaces and build trust towards the marketplace and its vendors include feedbacks and ratings. 18 In most marketplaces, buyers have to leave feedback and a rating after a purchase, similarly to what happens on legal online marketplaces. Additionally, marketplace administrators often act as vendor moderators by banning vendors or specific categories of products. Examples include DarkBay, where banned categories include human trafficking, contract killing and weapons, 46 or Monopoly marketplace, where COVID-19 fake vaccine listings were recently banned by moderators. 49 It is hard to estimate how many live dark web marketplaces currently exist. Recent reports include independent researcher Gwern, which identified 19 live platforms on April 22, 2020, 50 the website darknetstats, which registered 10 live "established" marketplaces on May 27, 2020, 51 and the already cited report 24 which crawled 20 different websites. Currently established marketplaces include Empire, Hydra and White House marketplaces. The listings used for our study were obtained by web crawling DWMs. Web crawling consists of extracting data from websites and is performed by specialized software. Web crawling DWMs is a challenging task because crawlers must bypass several protective layers. Most of the DWMs require authentication and some even require a direct invitation from a current member. Strong CAPTCHAs 52 are implemented to avoid otherwise easy and automated access to the online marketplace. Several research groups tried to overcome these challenges. For instance, the HTTrack software was used in; 16 a combination of PHP, the cURL library, and MySQL was proposed in; 53 the python library scrapy was adopted in; 54 and an automated methodology using the AppleScript language was utilized in. 55 There are currently very few open source tools available, 52, 56 often leaving companies and federal agencies to rely on commercial software. 57 Downloading content from DWMs remains a challenging task, which becomes even harder when the objective of the research study requires monitoring multiple marketplaces for a prolonged period of time. Our dataset contains listings crawled by 23 DWMs between January 1, 2020 and July 7, 2020 by Flashpoint Intelligence. 58 The pipeline of crawling consists of entering DWMs and downloading key Table 4 , "Time" and "Marketplace name" attributes are not present in this screenshot, while the "Quantity" attribute is not fixed by the vendor. attributes for each active listing, as highlighted in Figure 1 . Each DWM was crawled for at least 90 different days. We categorized the COVID-19 specific listings into five categories; PPE, medicines, medical frauds, tests, and ventilators. Only a fraction of the selected listings were actual COVID-19 specific listings, since mitigation measures to prevent COVID-19 spreading have also impacted illegal trades of other listings. For instance, a vendor might sell cocaine and mention shipping delays due to COVID-19. We included such cases in the category COVID-19 mentions. Categories and relative examples of the listings are presented in Table 1 . For details about data pre-processing, see Appendix A, where we explain how we select listings related to COVID-19 and how we classify them in categories. We remark that our pre-processing pipeline is biased towards the English language, and this constitutes a limitation of our work. Overall, our dataset includes a total of 472,372 unique listings, which can be observed a total of 4,088,840 times between January 1, 2020 and July 7, 2020. In Table 2 we report the breakdown of the number of unique listings and their total observations in each of the 23 DWMs. In 11 marketplaces (Black Guns, Cannabay, Darkseid, ElHerbolario, Genesis, Hydra, MEGA Darknet, Rocketr, Selly, Skimmer Device, and Venus Anonymous) we did not find any mention of COVID-19. This makes sense as these markets are less generalized and primarily focused on specific goods with specific listing text structure. A brief description of each marketplace together with its specialization can be found in Table 7 . In the remaining 12 marketplaces, there are a total of 4,010 unique listings related to COVID-19, which constitutes less than 1% of the entire dataset. These listings were mostly composed of drugs that reported discounts or delays in shipping due to COVID-19. Listings concerning more specific COVID-19 goods such as masks, ventilators, and tests were available on seven marketplaces (Connect, DarkBay/DBay, DarkMarket, Empire, CanadaHQ, White House, and Yellow Brick). There were 518 total COVID-19 specific listings in this markets which were observed 7,159 times during the analysed time period. We sampled tweets related to COVID-19 using a freely available dataset introduced in Chen et al. 22 We downloaded the tweets ID from the public github repository. We then used the provided script to recover the original tweets through the python library twarc. We studied the temporal evolution of the number of tweets mentioning selected keywords, like chloroquine. In line with our dataset of DWM listings, most of the tweets considered were written in English and the time period considered ranges from January 21, 2020 to July 3, 2020. We used the publicly available Wikipedia API 23 to collect data about the number of visits at specific pages related with COVID-19, like chloroquine. The Wikipedia search engine was case sensitive and we considered strings with the first letter uppercase, while the others lowercase. We looked for the number Wikipedia page visits in the English language from January 1, 2020 to July 7, 2020. We assessed the impact of COVID-19 on online illicit trade along three main criteria. First, we focused on the 7 marketplaces containing at least one COVID-19 specific listing, analysing their offers in terms of the categories PPE, medicines, medical frauds, tests, and ventilators, as introduced in Table 1 . Second, we considered the 12 marketplaces that included at least one listing in one of the categories in Table 1 , thus adding listings to the COVID-19 mentions category in our analysis. We investigated the relationship between major COVID-19 events, public attention, and the time evolution of the number of active listings. Third, we quantified the indirect impact that COVID-19 had on all 23 marketplaces under consideration by tracking the percentage of listings mentioning the themes of lockdown, delays and sales. We linked their frequency to major COVID-19 events. Here, we focus on the 518 COVID-19 specific listings present in our dataset, observed 7,159 times be- (78.8%) did not provide shipping information, and 13 (2.5%) did not disclose the listing price. The median price of PPE was 2 USD and they were the least expensive products, followed by medicines with 34 USD, tests with 70 USD, medical frauds with 200 USD, and ventilators with 1,400 USD. The distribution of prices for these categories can be found in Figure 2 (a), showing that many listings had a low price around a few USD or less and only few listings exceeded thousands or more USD. The cumulative value of the detected unique listings is 531, 413 USD, where we excluded listing with prices larger than 40, 000 USD due to manual inspection. When vendors post listings at high price this typical indicates they have halted sales of an item with the expectation of selling it again in the future. We remove these anomalously high priced listings since they would largely overestimate the sales price of the actually active listings. 18 The shipping information declared in the analysed listings involved a total of 12 countries or regions. Most of the vendors are willing to ship worldwide. Shipping from different continents is possible because some vendors explicitly declare that they have multiple warehouses across the globe, while shipping to any continent is done through specialized delivery services. The United States is the second largest exporter and shipping destination. Germany is the third largest exporter but no vendors explicitly mentioned it as a shipping destination. Complete shipping information is available in Figure 2 words. It illustrates that DWM vendors were particularly aware of the worldwide need of face masks because "face mask" were the most used words in the selected COVID-19 specific listings. The COVID-19 pandemic was referred to as either "coronavirus," "corona," "covid," or "covid19." Interestingly, we did not find any mention about the word "pandemic" itself. Among COVID-19 medicines, "hydroxychloroquine" and "chloroquine" were the most popular ones, with fewer mentions of "azithromycin," "medicated," and "medical" products in general. The Canadian HeadQuarters, and 5 in White House, as shown in Table 2 . The entire breakdown of the number of COVID-19 specific listings detected in each category is available in Figure 3 (b). In Figure 3 (c), we ranked the marketplaces for their share of vendors selling COVID-19 specific listings. The total number of vendors behind COVID-19 specific listings in our dataset is 131. Most vendors sold only one COVID-19 specific listing, while few of them sold more than ten different COVID-19 specific listings. In Appendix D, we analysed the distribution of COVID-19 specific listings for each vendor. We found that it was heterogeneous according to a power-law with an exponent equal to −2.0 and 80% of the vendors had less than 5 listings, as shown in Figure 7 . In DarkBay/DBay, more than 10% of the vendors were selling COVID-19 specific listings, while in Empire, The Canadian HeadQuarters, and White House this fraction was fewer than 1%. Finally, Figure 3 (d) shows that essentially no vendors specialised on COVID-19 products, with only 6 vendors selling more COVID-19 specific listings than unrelated ones, 4 of which actually sold just one COVID-19 specific listing overall in our dataset. The number of active unique listings evolved over time, as shown in Figure 4 (a). The first COVID-19 specific listing in our dataset appeared on January 28, 2020, following the Wuhan lockdown. 1 In March 2020, lockdowns in many countries 59, 60 corresponded to an increase in the number of these listings, whose number kept increasing until May 2020. In June and July 2020, when worldwide quarantine restrictions started to ease, 61 we observed a decreasing trend in the selected COVID-19 specific listings. Figure 4 (b) shows the evolution of the total number of observed PPE and medicines, the two most available COVID-19 specific listings in our dataset (see Table 3 ). PPE followed a trend compatible with the overall observations shown in Figure 4 (a), with a peak in May 2020 and a decrease afterwards, while COVID-19 medicines remained approximately stable from April 2020. The time evolution of the listing prices followed a different pattern. We considered the median price and its 95% confidence interval of active COVID-19 specific listings in Figure 4 the end of April, a vendor named "optimus," active on DarkBay, started selling large quantities of PPE at 1 USD, putting many online listings at the same time, thus drastically reducing the median price, which remained low until July. Overall, "optimus" had 91 PPE listings during the registered period. We also considered tweets and Wikipedia page visits as proxies for public attention. We focused our analysis on the PPE category and on the three most present medicines in our dataset: hydroxychloroquine, chloroquine and azitrhomycin. Figure 5 (a) shows that a first peak in public attention on PPE was reached in late January 2020 following the Wuhan lockdown 1 and a second peak in March 2020 63 when PPE listings started to appear in DWMs. The number of PPE listings reached their maximum in May 2020. After May, PPE listings steadily decreased along with public attention. It is worth noting that May also marked the end of the "first wave" of contagion in many European countries. 64 The last peak detected for the number of tweets in the beginning of July might be caused by the introduction of a new methodology to collect tweets in the freely available dataset we considered. 22 A similar relationship between mass media news, public attention, and DWMs was registered for the listings regarding the three considered medicines, as shown in Figures 5(b) We considered the indirect impact of COVID-19 on all the 23 DWMs in our dataset by looking at listings mentioning lockdown, using keywords "lockdown" or "quarantine," delay, using "delay" or "shipping problem," and sales, using "sale," "discount," or "special offer." Examples of listings reporting these keywords are available in Appendix B.2. events, such as lockdowns, 59, 60 one million worldwide cases, 67 and the situation in Europe starting to improve, 64 respectively, as shown in Figure 6(b) . A similar pattern was visible for the percentage of all listings mentioning sales. In addition, we observed that sales had a first peak corresponding to the New Year, which is a common practice of many in-person legal shops, as displayed in Figure 6 (c). Interestingly, despite observing that the increase in the percentage of all listings mentioning sales, delays, and lockdown followed major events related to the pandemic, not all of these listings also mentioned COVID-19. We further researched this by plotting which percentage of the relative listings also mentioned COVID-19 in Figure 6 (d In summary, we investigated the presence of listings related to COVID-19 in 23 DWMs, monitored over a six-month period in 2020. We considered COVID-19 mentions and COVID-19 specific listings, find- Our work corroborates previous findings and expands on them in several ways. The most extensive report to date, to the best of our knowledge, examined the presence of COVID-19 specific listings in 20 DWMs on one single day (April 3, 2020). 24 Despite a small subset of overlapping marketplaces between that report and our study, (DarkBay/DBay, DarkMarket, Empire, White House, and Yellow Brick) we both assessed that COVID-19 specific listings constituted less than 1% of the total listings in the DWM ecosystem. These listings were mostly PPE, followed by medicines and they were found in only a few DWMs, while non COVID-19 specific listings were widespread. An important novelty of the present study, compared to the existing literature, is the analysis of the temporal evolution of DWM behaviour and its relationship to public attention, as quantified through tweets and Wikipedia page visits. Following the Wuhan lockdown, 1 we observed a first peak in the public attention, and a corresponding emergence of the COVID-19 specific listings. A second peak in public attention occurred in March 2020, when quarantine measures were adopted by many European countries. 59, 60 Again, during the same period, the number of COVID-19 specific listings sharply increased. Finally, when worldwide quarantine began to easy 61 in many countries, in June and July 2020, we registered a decrease in public attention and in available COVID-19 specific listings. Listing prices correlated with both variations in public attention and individual choices of a few vendors. Median price experienced a sharp increase in March 2020, probably due to speculation, and then decreased in April due to the choice of a single vendor responsible for 91 listings, named "optimus." The vendor sold a large quantity of PPE at 1 USD only, which constituted the 37% of active PPE listings in April 2020. Finally, we observed an increase in the percentage of all listings citing delays in shipping and sale offers, which peaked in March, April, and May 2020. Similar to a prior work that found Wikipedia page visits of a given drug to be a good predictor for its demand in DWMs, 72 we provide further evidence that the DWM ecosystem is embedded in our society and behaves organically to social changes. 73 The DWM ecosystem swiftly reacted to the pandemic by offering goods in high demand, and even tried to fulfill desires through evident scams, for example by offering vaccines already in March 2020, when no tested vaccination existed. Our research shares some limitations with previous studies, namely that not all active DWMs were surveyed. For instance, we did not analyse 15 of the marketplaces explored in the previous report. 24 It must be noted, however, that the number of active marketplaces is constantly changing due to closures or new openings; 19 and obtaining full coverage is challenging due to the active efforts of DMWs to obstruct research studies and law enforcement investigations, for example through the use of CAPTCHAs. By revealing that DWMs listings of goods related to COVID-19 exist and that they are correlated with public attention, we highlight the need for a close monitoring of the online shadow economy in the future months. For example, we expect that initial delays in the availability of a cure and/or vaccine would dramatically increase public interest for the online shadow economy, posing concrete risks to public health. We plan to improve our analysis of DWM activity by increasing the number of monitored DWMs and conducting a more extensive analysis of the impact on the pandemic on overall DWM trade by considering changes in prices of non-COVID-19 specific listings, such as drugs, weapons or malware. We anticipate that our results and future work will help inform the efforts of public agencies focused on protecting consumer rights and health. 74 The COVID-19 online shadow economy Attribute of a listing Explanation "Listing body" Description of the listing as it appears in the DWM "Listing title" Title of the listing as it appears in the DWM "Marketplace name" Name of the DWM "Shipping information" Where the listing is declared to ship from and to "Time" When the listing is observed "Quantity" Quantity of the listing sold "Price" Price of listing "Vendor" Unique identifier of the vendor The listings appearing on the DWMs were crawled and stored according to selected attributes. While a brief explanation of these attributes is already presented in table 4, here we focus on those attributes which involved some pre-processing before the analysis, that is, "Shipping information," "Quantity," and "Price." The "Shipping information" attribute was initially stored considering what the vendor declared. Then, it was standardised among vendors to correct any misspellings, using the standard python library pycountry. Vendors may declare a specific country, like United States, a continent, like Europe, or the entire world, which we standardise here as worldwide. The "Quantity" attribute was instead retrieved from the title of the listing using Facebook open-source library Duckling, 75 then it was manually checked and corrected during an annotation process. The "Price" attribute on DWMs was displayed in the listings in various currencies, such as cryptocurrencies and fiat currencies. In order to standardise and properly compare listing prices, we converted prices to USD at the daily conversion rate. Rates were taken from Cryptocompare 76 for cryptocurrencies, and from the European Central Bank 77 for fiat currencies. The attributes "Listing body" and "Listing title" in table 4, representing the title and description of the listings, were used to select the COVID-19 categories in table 1. To this end, we prepared two sets of keywords as shown in T table 5. Every selected COVID-19 listing contained either a word in the "Listing body" that matched one keyword in the first set or a word in the "Listing title" that matched one keyword in the second set. The rationale behind this choice was that the listing title was usually more precise on the product sold, whereas the body might contain promotions of other items the vendor was selling in other listings. At the same time, the vendor might mention COVID-19 in the body for various reasons, which we analysed in the main text. In order to classify listings in either COVID-19 specific listings (that is, PPE, medicines, medical frauds, tests, ventilators) or COVID-19 mentions, we ran a regex query in google bigquery. We remark that the chosen method returned words containing a string equal to one of our keywords. For instance, with the keyword chloroquin, we detected also chloroquine and hydroxychloroquine. After this automatic filtering step, we manually checked the selected COVID-19 related listings to further improve the accuracy of our sample. In order to minimize human error, at least two authors of the present manuscript checked each of these listings. A limitation of our approach was that keywords considered were in English. Therefore, even if drug names such as chloroquine were common to many languages and we detected some listings in a non-English language, our sample of COVID-19 related listings was biased toward the English language. The most popular category of COVID-19 specific listings was PPE, which included mainly face masks. We detected that 91% of listings did not specify the amount of masks sold. Within those who declared the amount sold, we found listings selling small quantities of masks, like "KN95 Face Mask for Corona Virus box of 50" priced at 50 USD, while others proposed wholesale deals, as in "AFFORDABLE 20 BOXS OF SURGICAL FACE MASK (WHOLESALE PRICE)" in which 5000 masks were available at 2, 000 USD. The second most popular COVID-19 category was medicines, composed mostly by chloroquine, hydroxychloroquine, and azythromicin. Like PPE, 84% of the times vendors did not specify the quantity sold. When they did, it usually was for wholesale deals, as in "9000 tabs hydroxychloroquine 200mg (USA AND CANADA ONLY)" where 9,000 tabs were sold for 1,194 USD. The smallest quantity we detected was 50 pills "chloroquine 50pills for 250$," sold at 250 USD. We also noticed that vendors often specified the size of the pill, being it 200mg, 250mg, or 500mg. The azythromicin was usually sold together with hydroxychloroquine as a prescription against COVID-19. One example of it was "hydrox-ychloroquine sulfate 200mg and azithromycin 250mg," where an unknown quantity of these drugs was sold for 40 USD. In the COVID-19 category of medical frauds, the most prominent listings were vaccines. Despite at the moment of writing of this manuscript (July 2020), vaccines are far from being actually developed, they were sold in DWMs since March 2020. These listings included both low price vaccines like "complete order free shipment COVID19 VACCINE," sold at just 200 USD, or high price one like "Covid-19 Vaccine. Lets keep it low key for now," priced at 15, 000 USD. In addition, among the listings in the medical frauds category, one could find potentially dangerous illicit drug mixes with claimed curative power against COVID-19, like "Protect yourself from the corona virus:" a marijuana based drug mix supposedly helpful in recovery from coronavirus infection. Other medical frauds included a 300 USD "CORONAVIRUS DETECtOR DEVICE, SAVE LIVES NOW" or a 1, 000 USD "Buy CORONAVIRUS THERMO METER." Tests for COVID-19 were also moderately present in DWMs during the pandemic. for a price of 7,500 USD. The two listings in the ventilator category were ICU ventilators. They were advertising fundamental hospital instrument, such as, "ICU Respiratory Ventilators , Emergency Room Vents" sold at 800 USD or "BiPAP oxygen concentrator ventilato Amid Covid-19" for 2, 000 USD. We describe three examples of listings in the COVID-19 mentions category. The listing with title "Best Organic Virginia Bright Tobacco Premium quality 600g" refers to the lockdown in its body as "unfortunately we have to respect coronavirus lockdowns, in order to ensure as much security as possible, we had to choose one type of shiping that is unfortunately much more expensive while lockdowns last." Another listing with title "(Out of Stock! Lower Price for Pre-orders Only) Testosterone Enanthate 250mg/ml -10ml -Buy 4 Get 1," mentions in the body that they "are currently out of stock of this product due to our oil suppliers not being able to get their raw powders shipped to them because of the Coronavirus" and they "have lowered the price a little to help make up for this delay." A third listing mention a sale directly in the title "COVID-19 SPECIAL OFFER 1GR CROWN BOLIVIAN COCAINE 90% 65," and link the discount with the distress caused by the pandemic. In this Section we aim at providing a summary of the main events related to the pandemic, focusing on the ones cited in the main text and listed in table 6. This is by no means a complete summary of the COVID-19 pandemic timeline. The first event to gain international attention and make the public aware of the coronavirus was the decision from China to lockdown the city of Wuhan, first epicenter of the pandemic, on the January 23 2020. 1 The virus then found its way to Europe, where the first country to be heavily hit by the pandemic was Italy. The Italian government decided to lockdown the entire country on March 9 2020. 59 The virus rapidly spread in Europe and internationally, with cases appearing more and more in the In this Section we provide additional material that support our main findings. In table 7 we provide more details on the 23 dark web marketplaces considered in our study. In particular we indicate the main specialization of the markets, i.e., the main category of products sold. If it is "Mixed", it means that the marketplace is not specialised in any particular category of goods. In the description we instead put information on the markets, with more details where available. All this information has been researched and compiled by the authors, with particular help given by Flashpoint Intelligence. 58 In table 8 we provide a table reporting the different COVID-19 related medicines which were found in the listings. The medicines were selected as they have been found or claimed to be effective against COVID-19. 21 The number of listings related to each medicine is also reported, noting that some listings sell more than one medicine (e.g. listings selling both hydroxychloroquine and azitrhomycin). A timeline of the coronavirus pandemic WHO. Coronavirus disease (COVID-2019) situation reports The effect of human mobility and control measures on the COVID-19 epidemic in china Economic effects of coronavirus outbreak (COVID-19) on the world economy 4 novel coronavirus hurts the middle east and north africa through many channels Why toilet-paper demand spiked 845%, and how companies kept up with it The Wuhan coronavirus has led to a face mask shortage, with sellersnow offering masks at up to $7 apiece Woman reported to prosecutors for alcohol disinfectant at double price in japan Anti-price gouging laws, shortages, and covid-19: Big data insights from consumer searches drug markets impact of COVID-19 Tor: the second-generation onion router Darknet market mortality risks Bitcoin: a peer-to-peer electronic cash system Traveling the Silk Road: a measurement analysis of a large anonymous online marketplace United States of America : Vs. Ross William Ulbricht Measuring the longitudinal evolution of the online anonymous marketplace ecosystem Collective dynamics of dark web marketplaces Coronavirus disease (covid-19) advice for the public: when and how to use masks Coronavirus disease 2019 (covid-19): Emerging treatments Tracking social media discourse about the COVID-19 pandemic: development of a public coronavirus Twitter data set Availability of COVID-19 related products on Tor darknet markets. Australian Institute of Criminology What the dormouse said: how the sixties counterculture shaped the personal computer industry. Penguin Henrik Frystyk Nielsen, and Arthur Secret. The world-wide web Drugs 2.0: the web revolution that's changing how the world gets high 8 suspects arrested in online drug market sting Discussing illicit drugs in public internet forums: visibility, stigma, and pseudonymity Drugs on the dark net: how cryptomarkets are transforming the global trade in illicit drugs Use of Silk Road, the online drug marketplace, in the United Kingdom, Australia and the United States Lost on the Silk Road: online drug distribution and the cryptomarket Not an Ebay for drugs: the cryptomarket Silk Road as a paradigm shifting criminal innovation. Available at SSRN 2436643 Silk Road, the virtual drug marketplace: a single case study of user experiences Responsible vendors, intelligent consumers: Silk Road, the online revolution in drug trading I2p data communication system The dark net: self-regulation dynamics of illegal online markets for identities and related services An eu-focused analysis of drug supply on the alphabay marketplace. EMCDDA commissioned paper Dark webs wall street market and valhalla seized, six arrested Darknet takedown: authorities shutter online criminal market AlphaBay Analyzing the darknetmarkets subreddit for evolutions of tools and trends using lda topic modeling Coronavirus: dark web market bans drug dealers selling fake covid-19 vaccines Updated: list of dark net markets (tor & i2p) Dark net markets comparison chart Data capture and analysis of darknet markets Mining the dark web: drugs and fake ids Tor marketplaces exploratory data analysis: the drugs case A framework for more effective dark web marketplace investigations. Information Datacrypto: the dark net crawler and scraper. Software Program On day 1 of lockdown, italian officials urge citizens to abide by rules The New York Times Britain locks down to stem the coronavirus. more or less The New York Times The world reopens, despite skyrocketing coronavirus cases Remarks by president trump, vice president pence, and members of the coronavirus task force in press briefing Assessing the risks of "infodemics" in response to COVID-19 epidemics Covid-19: Europe sees hope in decline in new infections Ignoring expert opinion, trump again promotes use of hydroxychloroquine Trump is taking hydroxychloroquine Coronavirus: confirmed global cases pass one million On whatsapp, rumours, and lynchings. Economic & Political Weekly Onion.live: Darkbay's trust report Comparison uptime dark markets Predicting drug demand with wikipedia views: evidence from darknet markets The darknet and smarter crime: methods for investigating criminal entrepreneurs and the illicit drug economy Emcdda special report: Covid-19 and drugs drug supply via darknet markets Duckling open-source library Foreign exchange rates api with currency conversion New york has 5% of covid-19 cases worldwide as city becomes battlefront United states coronavirus (covid-19) death toll surpasses 100 Correspondence and requests for materials should be addressed to Andrea Baronchelli: Andrea.Baronchelli.1@city.ac.uk. The authors declare that they have no competing interests.