Understanding Face Morphing as a Threat to Digital Identities in Technological Development

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Face Morphing

Imagine that you are at your bank and waiting for your line to get your payment cheque cashed. You are in your routine thoughts and with a big smile you come to the payment counter. You know the person as you have been their customer for the last 3 years so, you smile and try to greet him. But instead of warmly greeting you back like always, he refrains and instructs you in a dry tone to visit the manager’s office as your cheque cannot be cashed due to some issue.

Startled at this response, you visit the manager’s office where he asks you questions in an interrogative tone which you don’t like being a premium client of this bank. Upon asking he tells you that you have made suspicious transactions in the last three months to risky personnel, one of them which is linked to a notorious drug cartel. Your head starts spinning as now you recall that your facial recognition and other credentials are hacked. You report this situation to law enforcement and they come up with a verdict that someone spoofed your account through face morphing where he used your pictures to create a new fake Identity and masked the transactions under your name.

How did you become a victim of this malicious act? Let’s find out in this blog and explore the prevention steps.

What is Face Morphing?

Face Morphing or Image morphing is a graphic technique that uses mix & merge phenomena to create a new face image. The resulting image through face morphing looks highly realistic and resembles the source pictures. Sophisticated graphical animation and image manipulation are the key processes involved in creating a high-res face morph.

Face Morphing Process Explained

  1. Acquiring Source Images

Face morphing first requires multiple face images of the same or different persons. If the target is to create an entirely new digital identity, then different source images are required. In this case, source images are obtained from a malicious actor who also mainly plots the morphing activity. The second image is from a victim who may be sometimes called an accomplice. This is because of the issue of consent to sharing images responsibly.

  1. Detecting Facial Features

Face morphing application software is programmed to detect facial features from any facial image that includes eyes, nose, lips, eyebrows, ears, etc. However, advanced morphing software is now enhanced and it can go deeper and detect features like wrinkles, facial hair, skin tone, etc.

  1. Deforming Images

Mainly, the mesh-based technique or linear interpolation is used to remove the facial features that are not needed and retain the needed ones. The structure of the target or source image is retained to create a realistic morph.

  1. Blending

Now, both the source images from the malicious actor and the accomplice are combined or blended. The morphing software application ensures that the images are transitioned smoothly and that the mismatch occurrence is reduced to the minimum.

  1. Rendering

In rendering the two intermediate frames of face images are generated that will create a seamless effect in facial morphing resulting in a new face image that can now be used to create a fake digital identity.

  1. Refinement

Final editing touches are given to the morph by graphic designing professionals and then the image is ready for spoof attacks.

What are Different Types of Face Morphing?

i) 3D Morphing

Image manipulation in 3-D images is the most trending technique used by identity fraudsters nowadays. 3-D representation of source images uses 3-D interpolation or 3D sculpting techniques to create highly realistic 3D face morphs. 

ii) Feature-Base Morphing

This morphing technique is focused on detecting and blending the facial features of face images. Facial features mainly include eyes, lips, nose, eyebrows, ears, chin, and facial structure. There can be other features involved as well.

iii) Mesh Morphing

This type of morphing uses an identifier mesh having nodes and lines to recognize faces from a video or images. It uses image manipulation via vertices of a mesh grid used to deform and then merge the facial features. It is mostly used in graphic design. 

iv) Cross-Dissolve Morphing

This technique slightly differs from linear and feature-base morphing or we can say that it is a blend of these two. It uses the texture of the two images to merge them through textural alignment.

v) Linear Morphing

It is the most basic morphing technique in which two linear images are morphed through their intermediate frames and facial features. The varying weights of images are merged according to the linear position of each image.

How to Detect and Prevent Face Morphing?

Detecting a face-morphing attack is a complicated job. High-tech morphing attacks are not easily detected by the naked eye and require technological advancements to do this job. For example, to detect 3D morphing the identity verification solution is required to have the feature of 3D morph detection. To standardize this, the National Institute of Standards and Technology (NIST) creates benchmarks for identity solution vendors and guides them in achieving perfection to detect face morphing and other threats. Thus, employing a cutting-edge anti-morphing IDV solution is critically important for protecting the digital facial biometric data of users.

Face Morphing Prevention Techniques

Despite the use of a robust identity verification solution, some responsibility lies on the users to secure their digital data from morph attacks. Users must get educated against face morphing, and its techniques and then create a self-precautionary defense line against malicious attacks. 

But since the bad actors are advancing every day, Identity Solutions must upscale their game against the morph attacks as well. 

KYC Identity Verification Solutions that use facial recognition should integrate the following features against face morphing attempts:

  1. Biometric Liveness Detection
  2. Facial Landmark Analysis
  3. AI Model Training
  4. Pixel Matching
  5. 3D Facial Recognition

To do so, facial recognition software providers should also consider elements like cost constraints, technological challenges, user privacy concerns, and achieving high levels of accuracy in detecting actual morphing. 

Final Word

Face Morphing poses a serious risk to the integrity of user digital identities. It can be used to wipe out a person’s account or to damage a person’s reputation. This threat is rising with the advent of AI and advancing 3D Models. Digital identity verification now requires a much stronger defense against identity theft and spoofing attacks including face morphing where the role of IDV solutions is vital in preventing this illicit act. Linear Morphing

It is the most basic morphing technique in which two linear images are morphed through their intermediate frames and facial features. The varying weights of images are merged according to the linear position of each image.

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