How can biometrics change the fight against carding? (Fingerprints, facial recognition, voice authentication)

[Student]

Carding is a type of fraud in which criminals use stolen bank card information (card number, CVV, cardholder name, etc.) to conduct unauthorized transactions, purchases, or withdrawals. Biometric technologies (fingerprints, facial recognition, voice authentication) offer powerful tools to combat this type of cybercrime. For educational purposes, we will examine how biometrics can change the approach to countering carding, including the mechanisms, advantages, limitations, and real-world examples.

1. How does biometrics help combat carding?​

Biometrics are based on a person's unique physiological or behavioral characteristics, which are extremely difficult to counterfeit or steal, unlike passwords, PIN codes, or card details. In the context of carding, biometrics are used to strengthen authentication and verification processes, minimizing the likelihood of unauthorized access.

1.1 Fingerprints​

• Mechanism: Fingerprint scanners analyze the unique patterns of papillary lines. They can be built into smartphones, POS terminals, or even biometric bank cards.
• Anti-carding application:
  • When paying in physical stores, the biometric card requires a fingerprint to activate the transaction, preventing the use of a stolen card without the physical presence of the owner.
  • In mobile banking applications (for example, for logging in or confirming transactions), fingerprints replace passwords, which can be compromised through phishing or keyloggers.
  • Even if a fraudster obtains the card details, without a fingerprint they will not be able to complete the transaction.
• Example: In 2019, Mastercard and a number of banks (such as NatWest) began testing biometric cards that use a built-in fingerprint scanner to confirm transactions.

1.2. Facial recognition​

• Mechanism: Modern systems (such as 3D facial scanning, as in Apple's Face ID) use infrared sensors and machine learning to create a unique facial map that is resistant to forgery using photographs or masks.
• Anti-carding application:
  • When shopping online, facial recognition can be used to verify the buyer's identity, especially in systems with 3D Secure (such as Verified by Visa or Mastercard SecureCode).
  • Facial recognition in banking mobile apps ensures fast and secure account login, preventing fraudsters from using stolen credentials.
  • Systems may block transactions if the person does not match the registered profile.
• Example: Apple Pay and Google Pay use facial recognition to authorize payments, making it virtually impossible to use stolen card data on devices without biometric verification.

1.3. Voice authentication​

• Mechanism: Analyzes unique voice characteristics such as timbre, intonation, and rhythm. Used primarily in call centers or voice interfaces for banking applications.
• Anti-carding application:
  • In banking call centers, voice authentication allows customers to be identified without having to ask security questions that could be compromised.
  • Can be used to confirm transactions in voice assistants or mobile applications.
  • Makes social engineering attacks more difficult, where fraudsters try to impersonate the account owner.
• Example: HSBC and Barclays have implemented voice authentication in their call centres, reducing customer verification time and improving security.

2. The benefits of biometrics in the fight against carding​

Biometrics offers a number of advantages that make it an effective anti-carding tool:

1. Uniqueness and complexity of counterfeiting:
   • Biometric data (fingerprints, face, voice) is unique to each person and difficult to replicate. Even if a fraudster obtains card details, without a biometric match, they will not be able to complete the transaction.
2. Protection against automated attacks:
   • Carders often use bots for mass testing of stolen cards (card stuffing). Biometrics require physical presence or unique data, making such attacks impossible.
3. Improving user experience:
   • Biometrics simplifies the authentication process: users don't need to remember complex passwords or enter one-time codes. This reduces the likelihood of using weak passwords that are easily cracked.
4. Integration with multi-factor authentication (MFA):
   • Biometrics can be part of MFA, combined with other factors (such as device ownership or knowledge of a PIN). This creates multi-layered security that significantly complicates card fraud.
5. Reduce reliance on sensitive data:
   • Traditional authentication methods (passwords, CVV codes) are easily stolen through phishing, skimming, or data leaks. Biometric data is harder to compromise, especially if it is stored locally on the device (for example, in the Secure Enclave chip on an iPhone).

3. Limitations and risks of biometrics​

Despite its advantages, biometrics is not a panacea and has limitations that are important to consider in the fight against carding:

1. Privacy and data leakage:
   • Biometric data, unlike passwords, cannot be changed. If a fingerprint or facial recognition database is hacked, the consequences are irreversible.
   • Solution: Store biometric data in encrypted form on the user's device (not in the cloud) and adhere to strict security standards (e.g. GDPR in the EU).
2. Risk of counterfeiting:
   • While biometric data is difficult to counterfeit, it is not impossible. For example:
     • Fingerprints can be copied using high-precision casts.
     • Facial recognition can be fooled by 3D masks or deepfakes.
     • Voice authentication is vulnerable to voice recordings or AI-based synthesized voices.
   • Solution: Use advanced technologies (e.g. 3D face scanning with depth sensors or liveness detection) and regularly update algorithms.
3. Limited availability:
   • Not all devices support biometric technologies (especially in developing countries or on older devices). This may hinder mass adoption.
   • Solution: Gradual implementation of biometrics with support for alternative authentication methods.
4. Legal and ethical issues:
   • In some countries (such as the EU), the use of biometric data is regulated by strict laws, such as the GDPR. Companies must obtain explicit consent from users and ensure transparency in their data processing.
   • Solution: Clearly inform users about how their data is collected, stored and used.
5. Technical limitations:
   • Biometric systems can produce false positives/negatives, especially in conditions of poor lighting, noise, or damaged skin.
   • Solution: Continuous improvement of algorithms and use of backup authentication methods.

4. Real-world examples and trends​

1. Biometric cards:
   • Mastercard and Visa are actively developing cards with built-in fingerprint scanners. These cards don't require a PIN and work even without an internet connection, making them resistant to skimming.
2. Mobile payments:
   • Payment systems such as Apple Pay, Google Pay, and Samsung Pay have integrated biometrics (fingerprints and facial recognition) to confirm transactions. This has become the standard for mobile payments, reducing the risk of carding.
3. Banking apps:
   • Many banks (for example, Chase, Wells Fargo, Sberbank) have implemented biometric authentication in their mobile apps, making it more difficult for fraudsters to access accounts even with stolen data.
4. Voice authentication in call centers:
   • Banks such as HSBC use voice biometrics to identify customers, reducing processing times and preventing social engineering fraud.
5. Trends:
   • Development of behavioral biometrics (analysis of typing patterns, mouse movements, or gait) as an additional level of protection.
   • Integrating biometrics with artificial intelligence to detect anomalies in transactions.
   • The growing popularity of "invisible" biometric systems that operate in the background without active user intervention.

5. Practical recommendations for the implementation of biometrics​

To effectively combat biometric carding, banks, payment systems, and companies must:

1. Ensure secure data storage:
   • Use local storage of biometric data on devices (e.g., in secure chips like the Secure Enclave) instead of centralized databases.
   • Use encryption and tokenization to protect data.
2. Combine with other methods:
   • Use biometrics as part of multi-factor authentication to minimize the risk of counterfeiting.
3. Invest in anti-counterfeiting technologies:
   • Implement liveness detection systems to prevent attacks using masks, photographs, or recordings.
4. Comply with the law:
   • Ensure that the use of biometrics complies with local data protection laws (e.g., GDPR, CCPA).
5. Train users:
   • Educate customers about the benefits and security of biometric technologies to increase trust and adoption.

6. Conclusion​

Biometric technologies (fingerprints, facial recognition, voice authentication) hold enormous potential in the fight against carding, as they make it more difficult for unauthorized access to financial data and transactions. Their implementation enhances security, improves the user experience, and reduces vulnerability to automated attacks. However, successful implementation requires robust data protection measures, counterfeit resistance, and compliance with legal requirements. As technologies evolve and integrate with artificial intelligence, biometrics will become an even more effective tool in the fight against cybercrime, including carding.

If you would like to delve deeper into any aspect (such as technical details or implementation examples), let me know!