Panel – Deep Dive into the Dark Web

Operational Resources
Dark Web
Training & Development
Jane Lee - Sift, Ralf Hornberger - Arvato Financial Solutions, Tobias Wieloch - Europol
May 12, 2021
Tobias Wieloch of Europol’s Cyber Crime Centre , Jane Lee of Sift, and Ralf Hornberger of Arvato Financial Solutions take a deep dive into the troubled waters of the dark web, and explore illegitimate credit card marketplaces, current trends in criminal activity, and the cryptocurrencies that power those activities. Other topics covered include the many successful law enforcement initiatives designed to combat these criminals, data points breaking down criminal activity on the dark web, and what it takes for a vendor to be targeted by law enforcement.

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Related Resources

Dec 20, 2022
Fraud and Risk Mitigation for Merchants in the Age of Crypto

Despite overall economic uncertainty and crypto volatility, consumer interest doesn’t seem to be waning.

In a survey of 1,000 people conducted by Bank of America, 30% of respondents reported that they had no plans to sell their crypto holdings in the next six months. What’s more, 39% and 34% of those surveyed cited that they have used crypto as a payment method to make online or in-person purchases, respectively. The crypto space continues to mature leading to implications for merchants wanting to ward off nefarious activity while enacting sound risk mitigation strategies.

As crypto becomes more widely adopted by consumers and accepted as a form of payment by businesses, merchants need to carefully consider how to adapt to this new form of currencyWhat’s more, as regulators enforce sanctions designed to curb the illicit use of crypto, proper digital identity verification procedures are more critical than ever in combatting bad actors while ensuring users can transact safely and securely.

This webinar explores why the relationship between merchants and consumers needs to be underpinned by trust and how organizations need to ensure fiat and crypto off and on ramps and transactions are safe and compliant.

Learning Objectives:

  • Understanding the intensifying interplay between fiat and crypto off and on ramps and the implications for merchants
  • Key factors to consider when making technology decisions with respect to identity verification and onboarding processes
  • Why evolving regulations that differ across jurisdictions call for agile practices and constant monitoring

Jun 22, 2022
eCommerce Fraud: How Fraudsters Use the Dark Web To ‘Warm Up the Shop’ and Fool Rules-Based Anti-Fraud Systems

With e-Commerce booming, merchants are increasingly turning to fraud intelligence companies to prevent fraudsters impacting their growth. While it’s true anti-fraud systems are becoming more sophisticated at detecting fraudsters - rules-based systems can be fooled. With all the tools and knowledge available on the dark web, even mid-level fraudsters can bypass security measures. All they need to do is mimic original account holders of stolen accounts and credit card details in a process called ‘warming up the shop’.
It all sounds too easy. And it can be. With stolen credit card details, e-Commerce accounts and the tools needed to attempt account takeovers (malware etc.) readily available for purchase on dark web marketplaces, half the work of the fraudster is already accomplished. Aside from patience, some additional tools to spoof digital fingerprints (unique identifiers of a user’s device setup, IP address, geo location etc.) and even legitimate browser cookie sessions are all available to buy online. One of the main tools used are anti-detect browsers, a fraudster tool resembling a regular internet browser, but packed with features to mask a user’s true identity and location, mimicking a regular user’s browsing session.
We aim to present to you how the process of ‘warming up the shop’ looks from start to finish, showing you some of the fraud tools available on the dark web to aid fraud attempts - you’ll be surprised how sleek and professional they appear, even giving legitimate companies' marketing campaigns a run for their money!
Imitation is never perfect. The perfect solution to prevent a successful ‘warm up’ attempt comes in the form of truly knowing your users (KYU) and understanding their interactions and behaviors. Advanced fraud solutions powered by machine learning models can effectively weed out fraudsters before they’ve had a chance to warm up. Join us to discover how.

Learning Objectives:

  1. To understand the long process of fraudsters ‘warming up the shop’ to bypass rules-based anti-fraud systems by acting as naturally as a regular customer as possible.
  2. Be aware of the tools and knowledge available on the dark web that allow fraudsters to fool rule-based fraud systems.
  3. How KYU Advanced fraud solutions powered by machine learning (ML) models can help you understand every user behavior and interaction - and prevent fraud from happening.
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