Facial recognition technology is a vital security tool that can help identify real human faces versus synthetic representations, such as deepfakes.
As your identity is more and more at risk in today’s digital communications environment, face and voice liveness detection and other biometric tools are built into iPhone security to help reduce your risk of fraud and identity theft.
What Is Liveness Detection?
Liveness detection is used in biometric security to help verify if a person is a live human being, rather than a fake image or video recording… It can be used in the process of facial recognition and/or voice recognition.
AI based scam calls are on the rise… Scams that sound legitimate never going to be worse than today. They’re only going to get more realistic and more frequent.
While you may be paranoid, which is good, the average customer service representative may be overwhelmed and just trying to move from call to call to get through their day.
As artificial intelligence provides cyber criminals with even greater tools for more dangerous and efficient methods of social engineering and cyber attacks, the integrity of your online user identity – and preventing others from spoofing your face or voice in a presentation attack – has never been more important.
Why Is Face Liveness Detection Important?
The importance of using liveness detection technology in the age of AI, cannot be overstated.
For instance, what if you want to create an AI avatar of yourself – or worse – someone makes one of you without you knowing… First, who owns that avatar, and second shouldn’t we make it impossible for that avatar to be used nefariously to access your sensitive accounts, such as healthcare and financial records.
There needs to be a way to tie the authentication of your identity with all of your important accounts to the physical reality of your real self for maximum security.
As such, we need a way to ensure that secure biometric authentication systems can differentiate between real individuals and synthetic representations, such as deepfakes.
Face and voice liveness detection can assist healthcare companies, financial institutions, cellular service providers, technology companies, as well as you and your family protect yourself against fraud while securing your personal identity.
Some ways face and voice liveness technologies can help better protect us, our identifies and our data are:
- Fraud Prevention: By ensuring that only live biometric data is accepted, liveness detection mitigates risks associated with identity theft and unauthorized access. This is particularly vital in sectors like banking and online services where security is paramount.
- Enhanced Security: Liveness increases the security of biometric systems, making them more robust against sophisticated spoofing techniques. This enhanced security is crucial as cybercriminals increasingly employ advanced methods to bypass traditional security measures
- Data and Privacy Protection: Liveness detection helps ensure that only genuine biometric data is utilized, thereby reducing the risk of misuse by threat actors, and reducing potential privacy violations through the use of deepfakes or unauthorized materials.
- User Experience: By streamlining the authentication process—eliminating the need for complex passwords or multiple security questions—liveness detection can improve overall user satisfaction while maintaining high security standards.
It should be emphasized that the evolution of face liveness detection will eventually move away from active liveness detection systems to passive systems which operate in the background, making it less intrusive and requiring fewer user actions.
How Does Face Liveness Detection Work?
Liveness detection uses specialized cameras to verify who you are, based on the “something you are” concept of multi-factor identity verification.1
Liveness detection uses hardware and software algorithms to analyze facial data… This helps prevent presentation attacks where a fraudster uses masks, photos, videos or voice recordings, perhaps combined with artificial intelligence software, to pass themselves off as you in order to commit fraud.
Liveness detection technologies employ various techniques to assess signs of life, which are crucial in preventing identity theft and fraud… These include, but may not be limited to:
- Skin texture analysis: Liveness focused algorithms scrutinize the skin’s texture and pores. Real human skin has unique characteristics, such as variations in tone, oiliness, translucency and texture, which may be absent in deepfakes.
- Natural movement analysis: Technology detects subtle movements like blinking or head tilting that are difficult for deepfake technology to replicate.
- Infrared and/or thermal imaging: Systems may incorporate infrared and/or thermal imaging through the use of temperature sensitive cameras to measure heat emissions from the face and head. Apple’s Face ID uses infrared and can capture your face in total darkness.2
- 3D Depth Mapping: Utilizes depth-sensing technologies to distinguish between a real face and flat images or videos.
- Behavioral biometrics: Analyzes user interactions, such as mouse movements or typing patterns, to identify anomalies that may indicate fraudulent activity.3
- Challenge/response tests: Asks users to perform certain actions, such as turning their heads or smiling or answering a question, such as a CAPTCHA.
How Does Apple's FaceID Facial Recognition System Work?
Apple added facial recognition with Face ID to replace TouchID in the iPhone around 2017.
Face ID facial recognition is enabled by the iPhone’s TrueDepth camera which uses advanced liveness detection to capture an accurate representation of your facial identity…
The TrueDepth camera projects and analyzes thousands of invisible laser dots onto your face to create a depth map… The iPhone also captures an infrared image of your face. Face ID settings can be made more secure by requiring your “attention”, meaning that in order for Face ID to work your eyes must be open and looking at the camera.
The advanced camera hardware combined with a software neural engine inside Apple chips (such as the A11, A12 Bionic, A12X Bionic, A13 Bionic, A14 Bionic, and A15 Bionic), which are protected within the Secure Enclave, uses the depth map and infrared image to create a mathematical representation of your face and compares that representation to the enrolled facial data.
While Face ID is used locally to authenticate a user to their iPhone device, such as when accessing the Apple Passwords app, and is not used by 3rd party services for biometric authentication beyond the iPhone app environment, I expect that Apple will expand its use of Face ID to beyond the iPhone to serve other digital identity verification applications, verifying them against a secure, centralized identity repository.
Face Liveness Technology Companies
In addition to Apple, other companies are developing liveness detection technologies as growing concerns about human identify verification grow.
These companies are developing technologies to help strengthen their verification systems and prevent identity fraud in areas beyond local device authentication, such as an iPhone… However, I would expect that in the future Apple will broaden the use of Face ID to external authentication systems, such as banking, healthcare, etc.
Below are some of the top companies offering liveness detection services:
IMHO, companies that interact with individuals, providing important daily services, such as healthcare, cellular communication, online banking and financial services, property ownership verification, bitcoin and digital assets, etc. should be required by law to incorporate not only strong multi-factor authentication (MFA) services, but also liveness detection in their systems.
I expect companies like Apple to continue to build out their identity verification tools so that our faces and/or voices can be used to authenticate us, while not being used by criminals using replicas, or synthetic humans, aka “deepfakes” of us.
Summary
As we fight an asymmetrical battle against artificial intelligence systems that can copy our faces and voices in seconds, liveness detection is becoming an essential component of modern biometric identity verification systems…
With its public commitment to focus on privacy and securing your data, I would expect Apple to broaden the use of its “Sign in with Apple” service, while incorporating Face ID and other biometric authentication tools, such as Apple Watch, to strengthen the ability for us to log into 3rd party apps and websites to offer proof of life.
Automated identity verification, particularly through face liveness detection, strengthens protection against identity fraud, enhances user experience, reduces stress and helps maintain user privacy.
As we increasingly rely on digital transactions and communications for everything we do, robust identity verification systems will be crucial in maintaining trust and security and will likely become even more critical in safeguarding digital identities.
Footnotes
- An authentication system that requires more than one distinct authentication factor for successful authentication. Multifactor authentication can be performed using a multifactor authenticator or by a combination of authenticators that provide different factors. The three authentication factors are something you know, something you have, and something you are.
- The main difference between thermal imaging and infrared is that thermal imaging creates images based on temperature differences, while infrared measures temperature directly.
- I could envision a world where an iPhone is paired with an Apple Watch to detect heart rate while also being used for a login using facial recognition with Face ID. Other authentication factors could be included, such as voice recognition "Hey Siri authenticate my voice" and other "challenge/response" tests in imporant verification scenarios.
