## 2 Taxonomy of Biometric De-Identification  
We start by introducing the definitions of _biometrics_, _traditional biometrics_, _soft biometrics_, _social behavioral biometrics_, and _emerging biometrics_. **Definition 1**. : _Biometrics: Biometrics are human characteristics that can be used to digitally identify a person to grant access to systems, devices, or data [11]._  
**Definition 2**. : _Traditional Biometrics: Traditional biometrics are defined as well-established biometrics that are categorized as either physiological (face, fingerprint, and iris) or behavioral (gait, voice, and signature) [11]._  
**Definition 3**. : _Soft Biometrics: The term soft biometrics is used to describe traits such as age, gender, ethnicity, height, weight, emotion, body shape, hair color, facial expression, linguistic and paralinguistic features, and tattoos, etc., that possess significantly lower uniqueness than traditional biometric traits [12]._  
**Definition 4**. : _Social Behavioral Biometrics: Social Behavioral Biometrics (SBB) is an identification of an actor (person or avatar) based on their social interactions and communication in different social settings [13]._  
**Definition 5**. : _Emerging Biometrics: Emerging biometrics are new biometric measures that have shown the prospect of enhancing the performance of the traditional biometrics by fusing these new biometric modalities with established ones [14]._  
Thus, social behavioral biometrics can be considered as one example of emerging biometrics. Sensor-based, emotion-based, or psychological traits-based user identification are others examples of new identification types. Current research into de-identification is highly dispersed. Hence, there has been no consistent method of classifying different approaches and reconciling various definitions of de-identification. In this review article, we categorize biometric de-identification into three classes based on the biometric type and the ability of a biometric system to identify a subject. The categories are as follows:  
1. Complete de-identification;
2. Soft biometric preserving de-identification; 1. Utility lost de-identification; 2. Utility retained de-identification;
3. Traditional biometric preserving de-identification. The proposed classifications of de-identification are discussed below. 1. **Complete De-identification:** Complete de-identification is the first category of de-identification research. A known problem of pair-wise constraint identification refers to a situation where a system can determine that two de-identified faces in a video belonging to the same individual by using hairstyle, clothing, dressing style, or other soft biometric features [5]. Thus, in addition to traditional biometric de-identification, soft biometric de-identification is also necessary. We define complete de-identification as a process where the biometric modality of a person is entirely de-identified, for instance, by being fully masked or obscured. Neither the identity of a person based on this biometric modality nor soft biometrics of the de-identified person can be recognized. This is true for human identification through visual inspection, as well as for a more common computer-based biometric system. Complete de-identification is used in mass media or police video footage, where sensitive information needs to be hidden [15]. 2. **Soft Biometric Preserving De-identification:** Soft biometric preserving de-identification is the second proposed category. It is a process of de-identifying a particular traditional biometric trait, while the soft biometric traits remain distinguishable. The purpose of such de-identification methods is to remove the ability to identify a person using the given biometric, while still retaining soft biometric traits. For example, this type of de-identification would prevent face recognition technologies from identifying an individual, while still retaining their gender or age information [16], making it possible for a user to post a natural-looking video message on a public forum anonymously.