Velocity abuse poses a serious threat to the e-commerce and retail sectors. Fraudsters exploit various aspects of online platforms, such as account creation, promotional offers, and credit card transactions to abuse the system and cause financial and reputational damage. It is crucial for e-commerce managers, security professionals, developers, stakeholders, and regulators to recognize and combat velocity abuse to maintain the integrity of online businesses.

To gain a better understanding of velocity abuse and its impact on e-commerce and retail, it is essential to familiarize oneself with the various tactics used by fraudsters. This article will present an in-depth dive into the strategies that businesses can employ to counteract this growing issue. By utilizing a combination of tried-and-true, as well as innovative technologies like Verisoul's user authentication platform, businesses can work together to secure their platforms, maintain customer trust, and mitigate potential financial losses.

In this essential guide for e-commerce managers, we will discuss the top five technical tactics proven to be effective in the fight against velocity abuse. These strategies encompass a wide range of tactics, including device and browser fingerprinting, impossible travel detection, network risk and datacenter detection, bot behavior biometrics AI, and advanced Captcha with automation framework detection. By understanding how each of these methods operates and assessing their potential benefits and drawbacks, e-commerce managers and other stakeholders can determine which methods are most appropriate for their specific needs.

As we explore each of these tactics in subsequent sections, keep in mind that a multi-layered approach to security is often the most effective way to safeguard an online business from velocity abuse. Successfully combatting this form of fraud requires a combination of vigilance, technological implementation, and constant adaptation to the ever-changing landscape of online fraud. Armed with this knowledge and the strategies presented in this guide, e-commerce managers and their teams will be well-equipped to make informed decisions regarding their company's security measures and reduce the risk of velocity abuse.

Strategy 1: Device and Browser Fingerprinting

What is Device and Browser Fingerprinting

Device and browser fingerprinting is the process of analyzing unique characteristics of a user's device and browser to differentiate genuine customers from fraudulent actors. This method enables e-commerce managers and security professionals to identify suspicious patterns of user behavior, which may indicate velocity abuse.

How Does it Work

This technique involves collecting data on device and browser properties, such as operating system versions, browser plugins, screen resolutions, and installed fonts. By gathering and analyzing this information, it becomes possible to create a unique "fingerprint" to determine if multiple accounts originate from the same device or if users are exhibiting suspicious activity patterns that may be indicative of fraud.

Pros & Cons

Pros:

1. Effectiveness: Device and browser fingerprinting is highly effective at identifying multiple account creations and account takeovers. This functionality enables e-commerce managers to spot fraudulent activities, such as users attempting to exploit promotional offers or rapidly creating new accounts for fraudulent purposes.

   
   

2. Passive monitoring: The technique does not require any active input or action from users, making it unobtrusive and seamless in its integration with online platforms.

   
   

Cons:

1. User privacy concerns: The data collection involved in device and browser fingerprinting may raise privacy concerns, especially if the gathered data is personally identifiable or improperly stored and managed.

   
   

2. Constant evolution: With browser and device properties changing over time, it may become challenging to maintain an accurate and up-to-date fingerprinting solution, as fraudsters can adapt their techniques to mimic the characteristics of legitimate users.

   
   

Tactical Implementation

E-commerce managers seeking to integrate device and browser fingerprinting as part of their fraud prevention strategy should take the following steps:

1. Choose a reliable solution: Select a reputable device and browser fingerprinting provider with a proven track record of effectively identifying fraudulent activity. This solution should offer comprehensive data collection and analysis capabilities, as well as ongoing updates to stay ahead of evasive fraud tactics.

   
   

2. Monitor and analyze fingerprints: Carefully analyze the collected device and browser fingerprints for unusual behavior patterns. Consider the frequency or recency of account logins, browser settings, and device property combinations to identify potential fraudsters.

   
   

3. Set appropriate thresholds and alerts: Based on your analysis, establish thresholds for flagging or blocking suspicious users. These thresholds should be adaptable to the unique needs of your business, balancing security with user experience. Regularly reevaluate and adjust these thresholds as needed to optimize your fraud detection capabilities.

   
   

By implementing the recommended steps, e-commerce managers can effectively leverage device and browser fingerprinting to mitigate the impact of velocity abuse on their online businesses. This strategy, combined with other technical tactics to prevent velocity abuse, will significantly improve the security and integrity of their platforms.

Strategy 2: Impossible Travel

What is Impossible Travel

Impossible travel is a method used to detect fraudulent activity by analyzing user activity patterns and geolocation information to identify instances where users appear to be in two physically distant locations within an improbable timeframe. This technique is particularly useful in spotting potential fraud, as cybercriminals often use tactics like IP spoofing or VPNs to hide their true location and quickly execute multiple transactions across different regions.

How Does it Work

To implement the impossible travel strategy, businesses must collect and store IP addresses and timestamps for all user transactions. By using IP geolocation data, it becomes possible to calculate the time-based distances between consecutive transactions made by a single user. For example, if a user placed an order from New York and another one from Los Angeles within a few minutes, it would be considered impossible travel, as physically traveling between the two cities in such a short time is not feasible.

Pros & Cons

Pros:

• Impossible travel detection can effectively prevent rapid cancellations and flash sale exploitation, as these types of fraud often involve multiple transactions from far-flung locations.
• This technique can also help to identify account takeovers in cases where a cybercriminal gains access to a user's account and attempts to make fraudulent transactions from a location other than the legitimate user's known location.

Cons:

• False positives can occur due to VPN usage or shared connections, as these systems can make the user's IP address appear to be from a different geographical location. However, false positives can be minimized through additional data points and anomaly detection algorithms.
• The accuracy of IP geolocation services can vary, sometimes causing a lack of precision in detecting impossible travel instances.

Tactical Implementation

To implement the impossible travel technique for detecting velocity abuse, businesses should follow these steps:

1. Collect and store IP addresses and timestamps for all user transactions: For each user transaction, log the IP address and the date and time of the transaction. This information will be crucial in impossible travel calculations.

   
   

2. Calculate time-based distances and compare with actual travel times: Analyze the transaction data to calculate the time it would take an individual to physically travel between the locations of consecutive transactions. Compare these calculated travel times to the timestamps of transactions to detect instances where the travel time would be improbable or impossible.

   
   

3. Flag or block transactions exceeding a predefined threshold of improbability: Set thresholds for what would be considered impossible travel, such as a transaction occurring more than 1,000 miles away within a window of 30 minutes. When an impossible travel instance is detected, flag the transaction for manual review or block the transaction altogether.

   
   

Ultimately, by leveraging the impossible travel strategy, e-commerce managers and retail business owners can effectively combat velocity abuse, reducing the risk of fraudulent activities and safeguarding their businesses' bottom line.

Strategy 3: Network Risk and Datacenter Detection

What is Network Risk and Datacenter Detection

Network Risk and Datacenter Detection refers to assessing risk levels associated with user networks and detecting datacenter-based IP addresses that might be involved in velocity abuse. By identifying and blocking potentially malicious traffic originating from these sources, e-commerce managers can better protect their online businesses from fraudulent activities.

How Does it Work

This tactic involves using network intelligence tools to actively monitor and track user traffic based on their IP addresses. By identifying suspicious networks or IP addresses associated with data centers, businesses can quickly block or flag potential fraud attempts. This method prevents attacks originating from sources like botnets, proxy networks, and VPNs, which are commonly used by fraudsters to disguise their identity and bypass security measures.

Pros & Cons

Pros:

1. Effectively combats card testing and unauthorized proxy/VPN usage: By blocking datacenter IP addresses and known suspicious networks, e-commerce managers can limit the opportunities for fraudsters to test stolen card credentials or bypass location and identity checks.

   
   

2. Proactive response to emerging threats: Continuously monitoring networks for any risk level changes enables businesses to stay one step ahead of cybercriminals and respond to threats more quickly.

   
   

3. Reduces reliance on reactive measures: Network risk analysis and datacenter detection reduce the need for manual investigation and response to fraudulent transactions, freeing up valuable resources for other critical tasks.

   
   

Cons:

1. Incomplete coverage: While this tactic can help detect many dangerous networks and datacenters, it may not be able to identify all risky sources or accurately determine the cause of suspicious activity.

   
   

2. Potential for false positives: Blocking IP addresses and networks en masse can sometimes lead to legitimate users being caught in the dragnet, causing frustration and a negative impact on the customer experience.

   
   

3. Evolving threats: As fraudsters develop new tactics and attack methods, businesses will need to stay current with the latest trends in network risk and datacenter detection to effectively combat these threats.

   
   

Tactical Implementation

• Use network threat intelligence solutions: Implement network threat intelligence platforms and services that provide database information, tools, and resources to identify, track, and monitor risky IP addresses and networks.

  
  

• Detect and block datacenter IP addresses: In addition to monitoring your own user traffic, actively search for and block IP addresses associated with data centers often used as a base for cyberattacks. These addresses are typically not used by regular customers, so blocking them poses minimal risk to business operations.

  
  

• Continuously update your database and risk parameters: New vulnerabilities, tactics, and threats are constantly emerging, so it's essential to keep tracking new network risk indicators, attack patterns, and malicious IP addresses. Regularly update your database and fine-tune your risk parameters to stay ahead of evolving fraud techniques.

  
  

By effectively detecting and monitoring network risk and datacenter IP addresses, e-commerce managers can mitigate some of the most devastating types of fraud that plague the industry. Stay abreast with the latest trends, tactics, technologies, and strategies to protect your business and ensure its ongoing success.

Strategy 4: Bot Behavior Biometrics AI

What is Bot Behavior Biometrics AI

Bot Behavior Biometrics AI refers to artificial intelligence-driven systems that specialize in analyzing biometrics and user behavior to detect and prevent bot activities or automated fraudulent attempts in e-commerce and retail websites. These technologies are designed to identify anomalies in user interactions, differentiate between genuine human customers and bots, and reduce the impact of velocity abuse.

How Does it Work

Bot Behavior Biometrics AI works by analyzing various aspects of user interactions, such as mouse movements, click rates, scrolling speed, and keystroke dynamics to detect and block automated fraudulent activities. The AI algorithms can process vast amounts of data in real-time, comparing user behavior patterns against known bot characteristics or historical data to identify potential fraud.

Pros & Cons

Pros:

• Highly effective at stopping card testing, bypassing CAPTCHA, and bot-enabled checkouts, which reduces the risk of velocity abuse.
• Can adapt and learn from new patterns and behaviors, enhancing accuracy and efficiency over time.
• Offers real-time detection and prevention of bot activities.

Cons:

• May require frequent fine-tuning and updates to adapt to evolving fraud tactics and advancements in bot technologies.
• Implementing AI-based solutions can be complex and require significant investment in infrastructure and resources.
• The possibility of false positives or negatives, as some sophisticated bots or human-operated frauds might exhibit behavior patterns similar to genuine users.

Tactical Implementation

Implementing Bot Behavior Biometrics AI within an e-commerce platform involves several steps:

1. Deploy AI-based biometric and behavioral analysis tools: Choose a reliable biometrics AI solution that can process and analyze your platform's user interactions in real-time and detect anomalies or suspicious activities.

   
   

2. Integrate with existing systems: Ensure that the biometrics AI solution is seamlessly integrated into your existing e-commerce platform, security infrastructure, and fraud prevention systems.

   
   

3. Monitor for irregular activity patterns: Continuously monitor and analyze user behavior patterns on your e-commerce platform, looking for any unusual or suspicious activities that could be indicative of bot activities or velocity abuse.

   
   

4. Set thresholds and alerts: Based on the analysis of user behavior and known bot characteristics, determine appropriate thresholds and alert levels for various risk scores. This can enable automated responses to potential threats, such as blocking access or initiating additional verification measures.

   
   

5. Periodic updates and maintenance: Regularly update the AI algorithms, databases, and any other related resources to ensure that the system stays up-to-date with the latest trends and developments in bot technologies, fraud tactics, and cybersecurity.

   
   

6. Evaluate performance and optimize: Regularly evaluate the performance of your AI-based biometrics solution, addressing any potential issues or areas for improvement. Optimize the algorithms based on new insights or changes in user behavior patterns to ensure ongoing effectiveness in combating velocity abuse.

   
   

Strategy 5: Advanced Captcha and Automation Framework Detection

What is Advanced Captcha and Automation Framework Detection

Advanced Captcha and Automation Framework Detection is a combination of advanced Captcha technologies and the detection of popular automation frameworks. Captcha is a security mechanism used to distinguish between human users and automated systems like bots by presenting challenges that are difficult for automated systems to complete. This method of fraud prevention is particularly effective in combatting velocity abuse by impeding automated systems involved in various forms of online fraud.

How Does it Work

Captcha technologies, such as Google's reCAPTCHA, deter bots and human-assisted fraud by presenting challenges that are typically difficult for automated systems to solve. These challenges include distorted text, image recognition tasks, or puzzles that require reasoning and problem-solving abilities. By combining this with the identification of popular automation frameworks, such as Selenium or PhantomJS, security professionals can monitor and block potential fraudulent activities stemming from automated traffic and tools.

Pros & Cons

• Pros:

  
  
  • Effective at preventing card testing, bypassing CAPTCHA, and bot-enabled checkouts.
  • Can substantially reduce the amount of automated fraud attempts on an e-commerce website, enhancing security and customer trust.
  • Regularly updating captchas with new challenges increases the difficulty for automated systems, limiting their ability to bypass security measures.
  
  

• Cons:

  
  
  • Some advanced bots may still be able to solve captchas or employ alternative methods to bypass them, requiring constant adaptation of security measures.
  • Implementation of Captcha can frustrate legitimate users, potentially affecting the user experience and causing inconvenience.
  • Captcha and automation framework detection might lead to false positives in blocking or flagging legitimate traffic.
  
  

Tactical Implementation

1. Implement advanced Captcha technologies: Deploy technologies like Google's reCAPTCHA, or other advanced Captcha systems to present challenges to users that are difficult for automated systems to bypass.

   
   

2. Regularly update Captchas: Keep updating captchas with new challenges to impede automated bypass attempts. Stay informed of the latest advancements in Captcha technology and implement them accordingly.

   
   

3. Identify usage of popular automation frameworks: Monitor user traffic for indications of the use of popular automation frameworks, such as Selenium or PhantomJS. Look for specific characteristics in user data, such as similar user agent strings, header inconsistencies, or unusual activity patterns that may indicate automated usage.

   
   

4. Monitor and block traffic displaying characteristics of automated frameworks: Once you have identified the signs of automation framework usage, flag and block users exhibiting these characteristics to stop potential cases of velocity abuse.

   
   

5. Continuously improve and monitor: Stay up-to-date with the latest trends and advancements in the security industry. Make sure to continuously update your Captcha technology and enhance framework detection capabilities to keep up with the evolving tactics and methodologies of fraudsters.

   
   

By implementing advanced Captcha and automation framework detection, e-commerce managers can significantly improve their security measures against velocity abuse and reduce the risk of fraudulent activities occurring on their platform. However, it's essential to stay informed and continuously adapt to the ever-evolving landscape of online fraud to safeguard your business and maintain customer trust.

Final Thoughts and Next Steps

As we've seen, velocity abuse is a growing concern for e-commerce and retail businesses. To protect your business from this type of fraud, it's essential to implement a combination of the top 5 technical tactics discussed in this article:

• Device and Browser Fingerprinting: Analyzing unique device and browser characteristics to differentiate genuine customers from fraudsters
• Impossible Travel: Inspecting user activity patterns and geolocation to detect physically improbable travel instances
• Network Risk and Datacenter Detection: Evaluating risk levels associated with user networks and detecting datacenter-based IP addresses
• Bot Behavior Biometrics AI: Using AI-driven systems that specialize in biometrics and behavioral analysis to detect bot activities
• Advanced Captcha and Automation Framework Detection: Integrating advanced Captcha technologies with the detection of popular automation frameworks

Staying up-to-date with the latest trends and technologies in fraud prevention is crucial in combating velocity abuse. It's important to continuously refine and optimize your security measures to stay ahead of malicious actors who are constantly evolving their tactics.

In addition to deploying these technical strategies, fostering a culture of security awareness within your organization is paramount. Train your team to understand the risks of velocity abuse, and ensure that communication lines remain open for sharing knowledge and information about emerging threats and best practices.

Lastly, consider partnering with a cybersecurity solution provider like Verisoul to facilitate user authentication and protect your customers' data. By implementing a robust array of fraud prevention tools and strategies, you can defend your business against velocity abuse and maintain the trust and confidence of your customers.