In this blog, we delve into the complexities of tackling the increasing problem of counterfeit goods online and explore how Open-Source Intelligence (OSINT) and social media intelligence (SOCMINT) can aid in the fight against these illicit activities.
The ever-evolving digital era has ushered in unprecedented convenience for consumers, allowing them to shop online from the tap of a screen. However, this surge in e-commerce has also given rise to a darker side: the proliferation of counterfeit merchandise. Organized crime groups exploit online platforms, including social media, to distribute fake products, jeopardizing brand reputation, consumer trust, and legitimate revenue.
As online purchases account for nearly 20% of all retail spending [1], the volume of counterfeit products being sold online is keeping pace with this growth, posing significant challenges for business owners.
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The Counterfeit Goods Market
While estimates vary, the annual sale of counterfeit products globally has been valued at nearly USD 464 billion dollars [2], representing 2.5% of world trade. Although counterfeiting might appear to only inflict economic damage by selling lower quality goods, the reality is that it can present considerable dangers to consumer health and safety. Driven by a motivation to lower costs, counterfeit goods, like medications, do not adhere to established quality and safety regulations with little concern shown for their customers or the many thousands of low-paid workers caught up in the dangerous world that manufactures counterfeit items.
Counterfeit products can drain market share, revenue, and legitimate businesses’ profits. Moreover, they can undermine consumer confidence in genuine brands if customers mistakenly attribute the substandard quality of fake goods to the original brand.
Business owners face complex challenges as the battle against counterfeit goods sold online intensifies. Constantly evolving tactics deployed by organized counterfeiters demand vigilance, collaboration, and innovative solutions.
A recent study [3] found counterfeit crime gangs using nefarious social media influencers to advertise fake goods, thereby streamlining the pathway for consumers to discover and acquire counterfeit merchandise. Research carried out by the UK’s Intellectual Property Office reported that 31% of males had purchased counterfeits following social media influencer endorsement [4]. Whether through neglect or ignorance of the products’ authenticity, these prominent social media figures have marketed counterfeit items to their vast audience of devoted followers, fuelling this illegal global trade.
Leveraging OSINT and SOCMINT
In an era of rapidly expanding online public forums, the tasks of monitoring marketplaces and multiple social media platforms for counterfeits, discovering their sellers, and identifying the networks behind them can no longer be effectively undertaken through manual methods alone.
The overwhelming amount of data on the internet poses a significant challenge for businesses as they strive to identify, authenticate, and discern valuable insights amidst the clutter. Employing Open-Source Intelligence (OSINT) tools can significantly improve their capability to track counterfeit goods and protect companies from fraudulent sellers. These investigative tools offer automated, focused data gathering and risk analysis, which can expedite investigations and help organizations stay one step ahead of threats to their brand.
UNVEILING NETWORKS OF ILLEGAL RESELLERS
Identifying the people and organizations behind the counterfeit goods market is a tedious and difficult task when the investigator must comb through thousands of followers and friends to uncover how they are connected.
Security Operations Centers (SOCs) and intelligence teams within organizations should utilize social media intelligence, along with automated analytical tools, to efficiently gather data that can help initiate investigations into counterfeit goods markets and criminal networks.
AUTOMATIC RISK DETECTION TO UNCOVER ILLICIT ACTIVITY
Manually sifting through extensive data can be overwhelming, often resulting in information overload for an intelligence team. Hence, the importance of automated identification of pertinent social media intelligence cannot be overstated. Artificial Intelligence (AI) and Machine Learning (ML) enabled analytics equip investigation teams with a solid framework for risk detection that can be tailored to identify information unique to an organization, such as phrases and names.
Critical information can also be found across social media posts on image-sharing sites. Logo detection and image analysis, can quickly filter thousands of online videos and images to identify specific instances where brand names and logos are fraudulently used across social media and other platforms. After collecting content, Fivecast ONYX automatically scans all images for text and concepts, enabling users to swiftly pinpoint keywords of interest that appear in this type of media.
Fivecast ONYX deploys advanced data collection and AI-enabled risk analytics to rapidly identify threats hidden in masses of digital data. Fivecast ONYX’s automated, repeatable, and ongoing risk assessment framework can be customized to detect counterfeit products appearing on social media, helping corporate intelligence teams identify potentially harmful fake goods and expose criminal networks.
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REFERENCES
[1] Potter Clarkson, https://www.potterclarkson.com/insights/how-does-counterfeiting-affect-brands/
[2] OCED, 2021, https://www.oecd.org/en/publications/global-trade-in-fakes_74c81154-en.html
[3] Taylor & Francis Online, 2023, https://www.tandfonline.com/doi/full/10.1080/01639625.2023.2233041
[4] Gov.Uk, 2024, https://www.gov.uk/government/publications/social-media-influencers-and-counterfeit-goods-wave-2/the-impact-of-complicit-social-media-influencers-on-males-consumption-of-counterfeit-goods-in-the-uk#key-findings
