The Future of Biometric Data Protection

The Rise and Challenges of Biometric Data in Digital Security

Biometric data, which includes unique physical traits such as fingerprints, facial patterns, and voice recognition, has become a key element of modern identity verification and access control systems. Over the past decade, its integration into everyday devices like smartphones and wearables, as well as large-scale national systems, has surged. This rapid adoption is driven by the need for more secure alternatives to traditional methods like passwords and ID cards, as biometric data offers a direct link to an individual’s unique traits, making it harder to forge or steal.

However, as biometric systems become essential in industries ranging from healthcare to finance, concerns around data privacy, misuse, and breaches have escalated. In 2023, the Federal Trade Commission (FTC) issued a warning following alarming reports of data misuse and privacy violations involving biometric systems, highlighting the need for stronger protections. A 2024 survey of 1,000 U.S. consumers revealed a sharp decline in trust toward tech companies handling biometric data—only 5% of respondents expressed confidence in 2024, a dramatic drop from 28% in 2022. With these growing concerns, the future of biometric data protection hinges on how well companies can safeguard this sensitive information and maintain transparency with users.

Why Biometric Data Protection Is Critical

As biometric data becomes more widely adopted, protecting it becomes increasingly critical due to its immutable nature.  Unlike passwords or other traditional forms of identification, biometric data such as fingerprints or facial recognition cannot be easily changed or replaced if compromised. This makes breaches involving biometric data potentially far more damaging.

For example, in 2023, a Trojan malware known as GoldPickaxe targeted facial recognition systems in Southeast Asia, stealing banking credentials and facial data. Hackers manipulated the stolen biometric data to create deepfakes, allowing them to access victims’ bank accounts and commit fraud. Similarly, in 2021, tax scammers in China exploited a government identity verification system, leading to the theft of over $76 million through fake tax invoices.

Cyberattacks on biometric systems are rising, and concerns over privacy persist, particularly with the rise of AI-driven deepfakes. Without stronger security measures, trust in biometric systems could erode in the coming years.

Why the Future of Biometrics Must Be Privacy-First 

To ensure long-term trust and adoption, biometric systems must place privacy at their core. This involves empowering users with greater control over how their data is handled, along with transparent consent mechanisms.

1. User Control

For biometric data protection to be truly effective, user control is paramount. Individuals must be able to determine who has access to their biometric data and for what purposes. Without clear control mechanisms, users may unknowingly risk their data being shared or misused. For example, Apple’s Face ID allows users to control its usage and even disable it at any time. This ensures that biometric data is shared only when necessary and only with the user’s explicit permission. By prioritizing user control, organizations not only promote accountability and transparency but also empower users with greater visibility into how their sensitive information is stored and protected.

2. Informed Consent

Equally important is obtaining informed consent before collecting any biometric data. Users should be fully aware of the scope, purpose, and potential risks involved before agreeing to share their biometric information. Without informed consent, the collection of biometric data infringes on individuals’ privacy rights. Regulatory frameworks, such as the EU’s General Data Protection Regulation (GDPR), enforce this by requiring organizations to obtain explicit consent and clearly explain how the data will be used and retained.

3. Right to Withdraw Consent

In addition to obtaining consent, individuals should have the ability to withdraw their consent at any time. This includes the right to request the deletion or anonymization of their biometric data. Regulations like the California Privacy Rights Act (CPRA) provide this right, allowing individuals to maintain control over their personal information even after it has been collected, ensuring that biometric data is handled in a privacy-first manner.

Current Trends and Technologies in Biometric Data Protection

While privacy-first principles are critical, several strategies are already in place to enhance biometric data protection, including:

1. Multi-Factor Authentication (MFA)

MFA combines biometric data with other forms of authentication, such as passwords or security tokens, to enhance security. This layered approach ensures that even if one factor is compromised, access is still protected by other authentication methods. For example, a user might input a password and then scan their fingerprint to verify their identity. This extra step reduces the risk of unauthorized access by adding multiple layers of security.

2. Encryption

Encrypting biometric data is an essential practice for protecting sensitive information. Encryption ensures that if biometric data, such as fingerprints or facial recognition data, is stolen, it is virtually useless without decryption keys. For example, Apple’s Face ID encrypts facial recognition data before storing it securely on the device, protecting users even if a breach occurs. Similarly, many financial institutions encrypt biometric data to ensure that any stolen information cannot be exploited.

3. Liveness Detection Systems

Liveness detection is a growing technology trend that helps differentiate between real biometric data and spoofs, such as photos or fake 3D models. For instance, facial recognition systems equipped with liveness detection can determine if the face presented is genuine. Tech giants like Microsoft have incorporated liveness detection into features like Windows Hello, adding an extra layer of biometric security to prevent unauthorized access.

4. On-device Processing and Storage

Processing and storing biometric data locally on a user’s device, rather than transmitting it to centralized servers, significantly reduces the risk of mass data breaches. This trend helps prevent large-scale exposure by limiting the data’s vulnerability to external threats. Apple’s Face ID, for example, processes and stores biometric data directly on the device, minimizing risks associated with cloud-based storage.

5. Biometric Template Protection Techniques

Biometric template protection involves securing the digital representation of a user’s biometric features. By aligning with security standards such as ISO/IEC JTC 1/SC, biometric templates can be securely stored and managed. If a template is compromised, it can be regenerated or replaced, ensuring that user security is maintained without compromising the biometric system’s integrity.

Privacy First Technologies for Biometric Data Protection

Building on current trends, future technologies are taking biometric protection to the next level by focusing on privacy. Here are some key advancements:

1. Quantum Encryption

As quantum computing advances, traditional cryptography may no longer be sufficient to protect sensitive data. Quantum encryption, utilizing principles such as Quantum Key Distribution (QKD), ensures that biometric data remains secure even in the face of quantum threats. Any interception of data is detectable, providing unparalleled protection. China’s successful demonstration of quantum encryption using the “Micius” satellite highlights the future potential of this technology in safeguarding sensitive biometric information.

2. Blockchain Technology

The decentralized nature of blockchain technology makes it a powerful tool for biometric data protection. Unlike centralized storage systems, blockchain spreads data across a network of nodes, reducing the risk of large-scale breaches. Blockchain’s immutability ensures that biometric data cannot be altered, while private blockchains or off-chain storage systems further enhance privacy by keeping sensitive biometric information off public networks.

3. Homomorphic Encryption

Homomorphic encryption allows biometric data to be processed without the need for decryption. This capability ensures that biometric authentication can occur without ever exposing raw data, significantly reducing the risk of data breaches and unauthorized access.

4. Federated Learning

Federated learning enables biometric systems to be trained across multiple devices or servers without transferring the actual data. This technique ensures that biometric data remains on the user’s device, reducing exposure to external threats. Only aggregated updates from devices are used to improve machine learning models, maintaining data privacy throughout the process.

5. Zero-Knowledge Proofs (ZKPs)

Zero-Knowledge Proofs  allow for the verification of biometric data without revealing the data itself. This privacy-preserving cryptographic method ensures that only the necessary information is shared, keeping the underlying biometric data secure from unauthorized access.

6. Biometric Tokenization

Tokenization replaces biometric identifiers with randomized tokens that are used for authentication. The original biometric data is either securely stored or deleted, while the token provides a secure alternative for transactions. Even if a token is intercepted, it cannot be reverse-engineered to recover the original biometric data, adding an additional layer of protection.

How Verifiable Credentials Eliminate the Need for Centralized Biometric Data Storage

One of the most promising privacy-first technologies is verifiable credentials (VCs), which eliminate the need for centralized storage of biometric data. Verifiable Credentials (VCs), offer a decentralized solution, allowing individuals to prove their identity or attributes without the need for storing raw biometric data in central systems. These cryptographically secure digital representations of identity ensure that sensitive data remains protected and verified without being exposed to vulnerabilities.

When biometric data is required for verification, there is typically an enrollment process where the biometric information, such as fingerprints, is captured and stored either locally on a device or in centralized databases. For authentication, the stored biometric template is compared with fresh data during the verification process.

With VCs, this model is transformed. A person’s biometric data is captured only once by a trusted authority, cryptographically signed, and issued as a verifiable credential. This credential is then stored in a digital wallet, controlled by the individual, rather than being held in a central repository. When authentication is needed, the user presents the credential along with a fresh biometric scan for verification, reducing the need to store the raw biometric data anywhere but the individual’s secure digital wallet.

This decentralized approach eliminates the need for central biometric data storage, drastically reducing the risk of breaches. Cryptographic signatures attached to biometric templates detect tampering easily, providing a secure alternative to traditional centralized storage.

Benefits of Leveraging Verifiable Credentials for Biometric Data Protection

Verifiable Credentials (VCs) offer several key benefits for protecting biometric data:

• Enhanced Privacy: With VCs, biometric data is stored securely and decentralized within the user’s digital wallet, making it less vulnerable to breaches often associated with centralized databases.
• Reduced Attack Surface: VCs distribute biometric information across user-controlled digital wallets, reducing the likelihood of successful attacks on a single repository, as there is no central target.
• User Control: Individuals maintain control over their biometric data, deciding when and how to share it, which significantly boosts user trust and minimizes data misuse.
• Tamper-Proof Authentication: The cryptographic signing of biometric data within a verifiable credential ensures that any tampering is immediately detectable, providing a secure and reliable verification method.

The Increasing Role of AI in Biometric Data Protection

In addition to privacy-first technologies, artificial intelligence (AI) is playing an increasingly important role in enhancing biometric data protection.

• Enhancing Biometric Authentication: AI improves the speed and accuracy of biometric authentication systems by continuously learning and adapting to changes in an individual’s appearance or environment, such as lighting conditions or slight variations in facial expressions. This adaptability ensures more reliable results than traditional systems, which may struggle with these inconsistencies.
• Anomaly Detection: AI-driven systems excel at monitoring biometric data usage in real-time, detecting unusual patterns or activities, such as repeated failed login attempts. This capability is essential for preventing unauthorized access to biometric databases, particularly in sensitive sectors like banking and healthcare, where security breaches can have significant consequences.
• Liveness Detection: AI enhances security by enabling liveness detection, ensuring that biometric data, such as a face or fingerprint, is collected from a live person rather than a photo, video, or 3D model. By assessing subtle physiological indicators, AI can better protect against spoofing attacks that attempt to use fake biometric data.
• Adaptive Security Measures: AI systems are not only reactive but also adaptive. When a biometric system detects unusual data or attempts to use fake credentials, AI can trigger additional security checks. This may include actions such as MFA, which helps reduce the risk of fraud or unauthorized access.

Addressing The Challenges of AI in Biometric Data Systems

While AI offers numerous benefits for biometric data protection, it also presents new challenges:

• Privacy Concerns: AI’s capability to collect, process, and analyze biometric data raises privacy concerns. Many users are unaware of how their data is stored or shared, leading to fears about misuse and unauthorized surveillance. In fact, 85% of consumers from a survey say they are concerned about sharing data with AI tools, and 49% of them have chosen not to use AI tools due to distrust.
• AI Bias: Bias in AI-powered biometric systems, especially facial recognition, is another concern. Studies have shown that these systems often struggle to identify people with darker skin tones or women as accurately as lighter-skinned men. This has led to misidentifications and instances of wrongful arrests, raising ethical concerns about AI’s fairness.
• Data Security Risks: AI systems processing biometric data are prime targets for cyberattacks. Given the immutable nature of biometric data, such as fingerprints or facial scans, recovery or replacement is nearly impossible if compromised. This makes robust security protocols essential to safeguard against breaches in AI-driven biometric systems.

AI continues to reshape biometric data protection, but to be fully effective, it must evolve to address challenges around privacy, bias, and security.

Existing Regulations and Global Standards For Biometric Data Protection

In response to the increasing adoption of biometric systems and the challenges posed by emerging technologies like AI, governments and international bodies have established regulatory frameworks to protect biometric data.

Key regulations like the EU’s General Data Protection Regulation (GDPR), California Privacy Rights Act (CPRA), and Illinois Biometric Information Privacy Act (BIPA) set stringent requirements for consent, data transparency, and security measures. These laws impose severe penalties for non-compliance, ensuring that businesses prioritize biometric data protection.

In addition to these national and state regulations, global standards play a pivotal role in shaping the future of biometric data protection. Standards set by international bodies like the International Organization for Standardization (ISO) and International Electrotechnical Commission (IEC) ensure that biometric systems operate securely, efficiently, and interoperably across various industries and regions. Committees such as ISO/IEC JTC 1/SC 37 are focused on continuously updating these standards, addressing emerging threats such as biometric data spoofing and unauthorized access.

Conclusion: The Future of Biometric Data Protection

Identity.com

Identity.com helps many businesses by providing their customers with a hassle-free identity verification process through our products. Our organization envisions a user-centric internet where individuals maintain control over their data. This commitment drives Identity.com to actively contribute to this future through innovative identity management systems and protocols.

As members of the World Wide Web Consortium (W3C), we uphold the standards for the World Wide Web and work towards a more secure and user-friendly online experience. Identity.com is an open-source ecosystem providing access to on-chain and secure identity verification. Our solutions improve the user experience and reduce onboarding friction through reusable and interoperable Gateway Passes. Please get in touch for more information about how we can help you with identity verification and general KYC processes using decentralized solutions.