Identity replacement technology

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Identity replacement technology is any technology that is used to cover up all or parts of a person's identity, either in real life or virtually. This can include face masks, face authentication technology, and deepfakes on the Internet that spread fake editing of videos and images. [1] Face replacement and identity masking are used by either criminals or law-abiding citizens. Identity replacement tech, when operated on by criminals, leads to heists or robbery activities. Law-abiding citizens utilize identity replacement technology to prevent government or various entities from tracking private information such as locations, social connections, and daily behaviors.

Contents

Online identity theft, information stealing, and deepfakes are all methods used by hackers to replace or alter the identity of a victim. Along with these hacking methods are some solutions: face liveness detection, obfuscation of crucial information, and location privacy obfuscation. More advanced obfuscation technology can cover up the location of a person through privacy protection. The main method to achieve these kinds of obfuscation is by replacing personal information such as the location of a person with anonymous identities and operators or trackers. [2] There is also research being done on the effectiveness and use of biometric identity authentication such as fingerprints and faces to replace personal identity authentication such as one's SSN.

For biotechnology identity replacement, gene sequencing and identity adjustments are common areas of research. With cutting-edge technology, it is possible to change the identity of a person or the identity of an offspring. [3] With the advancement of science comes the ethical issues of cloning, identity change, and societal and organizational transformations.

Features replacement

Features replacement technology is any technology that changes, alters, hides, or misrepresent a person's features. This can include feature replacements such as fingerprint replacement, face replacement, pupil authentication replacement, etc. The technology involved in features replacement ranges from masking to creating 3D videos and images. [4]

Criminal uses

Example of facial replacement masks that could be used to hide someone's identity Vendetta-mask.jpg
Example of facial replacement masks that could be used to hide someone's identity

A variety of technologies attempt to fool facial recognition software by the use of anti-facial recognition masks. [5] 3D masks that replace body features, usually faces, can be made from materials such as plastic, cotton, leather, etc. These identity masks can range from realistic imitations of a person to unrealistic characters that hide the identity of an individual. Criminals and hackers tend to use a spectrum of masks depending on their intended objectives of the crime and other environmental factors. Usually, if a crime involves more planning and execution, criminals and hackers put more effort into creating their 3d masks. [6]

There are many intended purposes for feature replacements. Cyber criminals or real-life criminals use masks or 3D generated images of a mask to hide from security systems or pass through security checks. They usually do this finding the identity of a victim who has access to certain security systems. Then, criminals wear masks in public to conduct fraud and passes through security systems as the victim of the identity theft. [6] This usage of masks and 3D printed items to cover certain body features while conducting crime is illegal under laws like anti-mask laws. [7]

Other reasons for features replacement

Another use of face replacement technology is to hide one's identity from third-party trackers, monitors, and government officials. [8] Although uncommonly used by individuals, this method of hiding one's identity (either online or in-person) is mainly used for hiding from government tracking, for entertainment purposes, and for religious purposes. People may decide to wear a mask in-doors to prevent government tracking, for example.

Deepfakes, spoofing, and anti-spoofing

Deepfakes and synthetic media

Deepfake usages

Deepfakes, a type of identity replacement technology, are pictures or video edits that replace the identity of a person in the picture or the video. This digital forgery is used to manipulate informations, defame people, and blackmail individuals. Through editing techniques such as face replacement and pixel or coloration implant, deepfakes can resemble the real image closely. [1]

Deepfakes are classified into four types of identity manipulations: face synthesis, identity swap, attribute manipulation, and expression swap. [6] Some more specific examples include face swapping, lip syncing, motion transfer, and audio generation. [9] Although a more common usage of synthetic media or deepfakes is political disinformation, a less known phenomenon is financial fraud committed by cybercriminals who use deepfakes to steal financial data and profit from doing so. Hackers and criminals use deepfakes to penetrate social media accounts, security systems of banks, and individual financial information of wealthy individuals. [1] Two scenarios that are used by hackers and manipulators include narrowcast and broadcast. Some deepfake techniques include deepfake voice phishing, fabricated private marks, and synthetic social media profiles that contain profiles of fake identities. According to research, [1] deepfake prevention requires collaboration from key stakeholder such as internal firm employees, industry-wide experts, and multi-stakeholder groups.

Technology used to deter deepfakes

Some possible methods of deterring deepfakes include early detection of face mismatches, individual feature analysis of the face, identity confirmation of images or videos, and techniques that utilize multi-feature analysis that pinpoint face liveness, etc. [6] There is further research being done on deepfakes techniques such as face morphing and face de-identification. However, deepfake prevention techniques tend to be worse at identifying more advanced deepfakes, identification methods sometimes fail to recognize unseen conditions not related to facial analysis, and databases and technology must be up-to-date based on evolving deepfake techniques.

Deepfakes can be used as weapons to spread misinformation and threaten democratic systems through identity replacement strategies. Some deepfakes, due to low cost and ease of usage, can be used to replace identities and spread misinformation across nations and the international landscape effectively. [9] Hackers can use bots or deepfakes that spread propaganda and disinformation to adversaries, and these attempts could challenge democratic processes internationally. The public will be distrustful due to the potential use of deepfakes by politicians or outside countries.

Spoofing and anti-spoofing

Spoofing process that shows the flow of attack by malicious user to penetrate a user's account or profile information. ARP Spoofing.svg
Spoofing process that shows the flow of attack by malicious user to penetrate a user's account or profile information.

Spoofing

Spoofing, a concept related to deepfake, is a method of hacking and identity manipulation by impersonating as a known source trusted by a spoof target or system of security. Spoofing attacks can be easily launched due to common uses of face recognition systems in mobile device unlocking. [10] One way the hackers get into the system is by using a synthetic-forged biometric that fools sensors and grants a different identity to the hacker who passes through as the real identity. [11]

Spoofing can also involve fake physical artifacts such as fake printouts of masks and fingers that hackers use to manipulate biometric authentication technology. [8] Due to spoofing attempts on a mass scale, there are global political, ethical, and economical threats that goes beyond a country's borders. Mass crimes involving cybersecurity breaches, political hacking, and personal identity thieving can cause damage to the international landscape. [8]

Anti-spoofing techniques

Payment information, personal information, and biometric information are all potential exploitation sources performed on by hackers. [10] There are both feature level and sensor level anti-spoofing techniques. The goal of anti-spoofing is to deter illegitimate users from accessing to important and personal information. 4 main groups of anti-spoofing techniques are widely used by cybersecurity experts: motion analysis, texture analysis, image quality analysis, and hardware based analysis that integrates software components. [10] Another anti-spoofing technique is using color texture to analyze the joint color-texture density of facial features in images and videos. [12] By comparing across databases using replay videos of spoof attacks, many of these methods are able to detect liveness of faces and facial symmetry under a controlled environment. [12]

Email using spoof techniques SPOOFED-EMAIL.jpg
Email using spoof techniques

Anti-spoofing and deepfake identification are prone to errors and attacks. For example, one model of attentional adversarial network to generate fake images that match the original pictures in terms of features, face strength, and semantic information. [13] One drawback of such an adversarial network model is it analyzes only one attack target; However, research is being done on using various models to target multiple attacks. [13] Some other shortcomings of anti-spoofing techniques include failure to detect spoofing across databases, failure to apply to real life scenarios, and performance issues related to the limits of the technologies involved. [11]

Identity change and biotech enhancement

Biotech enhancement

Gene sequencing and gene therapy are cutting-edge technology used by biotech researchers to discover ways of altering the identities or genes of offsprings and humans. With gene alternating and features enhancement, one can change the structural identities of offsprings. Another related concept is cloning, a more futuristic concept about replicating human beings. [3]

On a broader level, identity change leads to social transformation. [14] Identity change and organization transformations occur sometimes at the same time. For example, there is profound socio-political change related to collective and individual identity change in Ireland. Identity change is also associated with economical, political, and social factors related to the changing environment. Individuals maintain the right to make personal choices, but these choices are often affected by one's surroundings and one's immediate environment. [14] Enhancement and alteration of the human body and identity is thus connected to broader social transformations. If society changes and evolves, then individuals may choose to evolve with it. Generational factors are also considered by researchers as biotech evolves and advances.

Ethical concerns of biotech enhancement

Fundamentally, some current objections to enhancement biotech include questions about authenticity of biotech enhancement and fundamental attributes and values of being human. Some key concerns include safety, ethical distributions, and identity traits violations. [3] Current biotech research is seeking to expand upon what human identity means, the connection between gene alteration and human enhancement, generational offspring alterations. More research is needed in this realm of biotechnology research for scientists to determine the viability and ethical issues revolving around advanced biotechnology. [3]

Face authentication and biometric identification

Biometric identifications, including face authentication technology, is used by firms, governments, and various other organizations for security checks and personal identification. [8] This procedure and technology is especially important to protect private materials and information of a firm or government. Due to evolving security technology, Biometric authentication methods are replacing physical copies of IDs, numbers like SSN, and personal information written on paper.

3D sensor analysis to test face authenticity

3D cameras and depth analysis can be used to detect spoofing and fraudulent data. [4] Biometric identifications with a wide range of depth and flexility can aid the detection of spoofing attempts by hackers and identity thieves. Liveness assurance and authentication of faces can help prevent face identity manipulation and forgery in that liveness detection of the face can use color, depth, angle of facial features, and other factors to distinguish between fake and real faces. Due to the ease of making a 3D mask and creating deepfakes online, fake identities is increasingly common in the tech industry. Some common methods used to achieve face authentication results include: SVM classifiers, image quality assessment, pupil tracking and color texture analysis. [4] Biometric identification technology with a higher flexibility leads to better detection of spoofing attacks.

3D face reconstruction and face alignment can aid the use of biometric identification systems when authenticating identities of individuals. An end-to-end method called Position Map Regression Network is used to reconstruct 3D facial features from the 3D space such as from an image of a person. Some key metrics in measuring the effectiveness of alignment and reconstruction include face reconstruction speed, runtime of alignments and accuracy of facial alignment compared to original image. [15] Through restructuring 3D facial structures using density to align faces, position maps can convert a 3D face into a 2D image based on a UV plain analysis. 3D shapes are acquired by 3D sensors and specific features within the face shape are acquired by the sensors to retrieve information. [16] Convolutional neural networks are trained to extract facial and semantic information from the 3D image to the 2D image with a process called regression. [15] Overall, this position-map method of facial reconstruction and alignment can be used in cybersecurity authentication, biometric verification, and identity matching.

Fingerprint biometric identification

Fingerprint patterns in identification and matching Fingerprint Types and Patterns.png
Fingerprint patterns in identification and matching

Fingerprinting is also a biometric identification method researched on by cybersecurity firms and governments. Fingerprint verification can be used to counter identity theft or potential fraud just like face authentication technologies. One study uses a minutiae-extraction algorithm to develop an identity-authentication system based on how it extracts data and verifiable information from the fingerprint scan. [17] This model is based on alignment, where it matches inputs to stored template to verify the identity of someone faster and more accurately. The goal of all biometric authentication methods, including fingerprint identification, is to have accurate and speedy responses in authenticating data. Systems and alignment technologies are constantly updated to achieve better results. Some drawbacks of fingerprint identification are large distortions in poor image quality, straight line deformations, vague transformations that affects authentication quality, and missing minutiae for some parts of an image. [17] However, multiple biometric authentication tools could be used, such as face and fingerprint, in order to obtain better and more accurate performances.

Fingerprint sensing identification system Ultrasonic-fingerprint-scanner-Qualcomm-Sense-ID.jpg
Fingerprint sensing identification system

Applications of 3D sensors and biometrics

The components of 3d sensors such as key electronic parts and sensor systems are increasingly made smaller and better by emphasizing compactness of sensors, effectiveness of detecting shapes, portability, strength of imaging, etc. [16] 3D imaging and optical sensor can be expensive, but the cost can be decreased when manufacturers and suppliers make individual sensor components cheaper and more flexible to fit a variety of sensors and cameras. Virtual renders and prototyping tools are integrated into 3D sensor and camera systems to aid with facial reconstruction, identity search, and shape designs. 3D sensors can be made to form sensor systems where the entire system is more effective at capture an image compared to single sensors or cameras. [16] There are applications for 3D sensors such as in manufacturing, optical uses, and robotic applications. Key industries that could utilize 3d cameras include robotics, law enforcements, automatic authentication systems, and product development.

Identity theft

Identity theft is the concept when a thief steals the identity of a victim and portrays oneself as the victim's identity. Identity theft has many implications both on a small and large scale. Individual identity theft can be limited to a single person when the identity thief takes on the identity of that victim. [18] The reason for identity theft might include pleasure of entertainment, malicious hacking, settling revenge, or for political purposes of sabotage. Mass scale identity theft can involve political sabotage, financial and economical heists and crimes, and social changes for the worse.

Identity theft and consumer payment

Identity theft and identity replacement has shaped and affected consumer spending over the past years in the financial world. One method used to analyze identity theft is to map identity theft incidents to determine geographical locations, environmental factors, and purposes of identity theft. Payment instruments used by different types of payment systems can affect how identity theft is used to obtain financial information and commit financial fraud. [18] Identity theft has an implication for consumer payment behaviors and adoptions. Although customers have different payment methods, geographical areas with more identity theft occurrences tend to have an increased use of payment methods such as money orders, travelers’ check, prepaid cards, and credit card payments. Electronic payments are widely used by consumers given society's evolving landscape of payment technology. However, these payment systems, including transactions of checks, cards, and cash, require periodic updates to keep up with evolving ways of identity theft. [19]

Identity Theft process in financial transactions where the thief uses someone else's account to perform transactions. Figure 2 Example of a Successful Identity Theft Refund Fraud Attempt (28356288536).jpg
Identity Theft process in financial transactions where the thief uses someone else's account to perform transactions.

Given our current economy of transactions involving customer data, more opportunities are created for fraudulent transactions since more consumers are shopping online and conducting financial transactions online. [19] A thief could hack data related to common financial derivatives and items such as product payments, loans, mortgages, stocks, options tradin g, etc. [19] One way identity theft can happen is when the thief tries to obtain a service or product but pays it with someone else's financial data or account information. This fraudulent transaction will attribute the cost of the transaction to the identity thief victim. The victim's identity could be used multiple times by different thieves using similar or different identity theft methods. Some solutions to such problems include consumer protections, credit freezes if fraud occurs, credit verification, and penalties and enforcements.

Identity theft in politics

Identity theft can also involve political manipulations and hacking on a large scale that is detrimental to the political wellbeing of international politics. [8] Identity thieves can use identity replacement methods such as biometric replacement, face masks, deepfakes, and personal information stealing to conduct political sabotages. For example, an identity thief could conduct voter fraud by imposing as one or more individuals who cast ballots. The thief could also hack the social media account of a politician and post scandals or defamation about that politician.

Obfuscation and identity privacy protection

Definition of obfuscation

Obfuscation has a technical meaning of code protection and making coding patterns, structures, and lines anonymous to everyone but the code programmer. This way, the programmer deters incoming hacks and shell-injection attacks methods. Another use of obfuscation is protecting a person's identity online, such as protection of privacy, location, and behaviors. [2]

Morse code using obfuscation techniques Obfuscated Morse code.png
Morse code using obfuscation techniques

Methods of obfuscation

Obfuscation operators can be used to determine distribution areas, privacy protections, and location preferences. Probabilistic fundamentals such as the joint distribution function are used to test out obfuscation operators and how operators can be used to protect location privacy of individuals without sacrificing certain app features and efficiencies. [2] Thus, obfuscation can be used to make location and related information anonymous and useless to potential hackers who are trying to breach the privacy of individuals. Adversary models can be used to form combinations of operators to test the viability of obfuscation operators based on adversary awareness, utility functions, and robustness of operator families. [2]

Another obfuscation privacy protection method protects images online and through social media. [13] The targeted-identity-protection-iterative method(TIP-IM) is used for this type of image-privacy protection. The method is to feed various adversarial models into TIP-IM and look at the performance of adversarial networks. By simulating an identity-protection system, the method identifies an adversarial network that interacts with privacy protection results. [20] Thus, the TIP-IM can prevent hackers' unauthorized access to images, accounts, and systems that have sensitive information. There is also a trade-off between effectiveness and naturalness of the protected face and identity images: naturalness of faces decreases as image protection becomes more effective. [13]

Obfuscation Categories

Obfuscation can be divided into three categories: construction, empirical, and construction and empirical combination. Mapping obfuscation techniques involves analysis in data, layout, control, and preventive structures of applications. [21] By diversifying systems and obfuscation of data through system analysis, data scientists and security experts can make it harder for hackers to breach a system's security and privacy settings. Virtualization systems are used by cybersecurity experts to test the effects of various obfuscation techniques on potential cyber attacks. Different cyber attacks on private information require different diversification and obfuscation methods. Thus, a combination of multiple obfuscation methods such as code blocking, location privacy protection, identity replacements can be used. Some further studies in the field of obfuscation include analysis on diversification methods and performing tests on different virtual environments such as cloud and trusted computing. [21]

Olympus: an example of obfuscation technology

One study formed a system of obfuscation operators called Olympus, a system of managing data and protecting privacy of individuals on applications. [22] Olympus's goal is to maintain existing data structures and functionality of the applications while also protecting the privacy of personal information uploaded onto the testing applications. These data usually come from sensors and are uploaded onto the application where it's analyzed. Through obfuscation operators and certain combinations of them, an individual's private data can be protected while also being analyzed. Information categories like SSN, birth dates, home locations, age, gender, race, and income that are sensitive to data-stealing and identity thieving are protected. Olympus is an attempt to apply privacy protection to real world applications. By forming adversarial networks between utility requirements and privacy through weighing the tradeoffs between them, data's usability is kept. [22]

See also

Related Research Articles

<span class="mw-page-title-main">Authentication</span> Act of proving an assertion, often the identity of a computer system user

Authentication is the act of proving an assertion, such as the identity of a computer system user. In contrast with identification, the act of indicating a person or thing's identity, authentication is the process of verifying that identity. It might involve validating personal identity documents, verifying the authenticity of a website with a digital certificate, determining the age of an artifact by carbon dating, or ensuring that a product or document is not counterfeit.

Biometrics are body measurements and calculations related to human characteristics. Biometric authentication is used in computer science as a form of identification and access control. It is also used to identify individuals in groups that are under surveillance.

<span class="mw-page-title-main">Iris recognition</span> Method of biometric identification

Iris recognition is an automated method of biometric identification that uses mathematical pattern-recognition techniques on video images of one or both of the irises of an individual's eyes, whose complex patterns are unique, stable, and can be seen from some distance. The discriminating powers of all biometric technologies depend on the amount of entropy they are able to encode and use in matching. Iris recognition is exceptional in this regard, enabling the avoidance of "collisions" even in cross-comparisons across massive populations. Its major limitation is that image acquisition from distances greater than a meter or two, or without cooperation, can be very difficult. However, the technology is in development and iris recognition can be accomplished from even up to 10 meters away or in a live camera feed.

<span class="mw-page-title-main">Facial recognition system</span> Technology capable of matching a face from an image against a database of faces

A facial recognition system is a technology potentially capable of matching a human face from a digital image or a video frame against a database of faces. Such a system is typically employed to authenticate users through ID verification services, and works by pinpointing and measuring facial features from a given image.

Data security means protecting digital data, such as those in a database, from destructive forces and from the unwanted actions of unauthorized users, such as a cyberattack or a data breach.

Living in the intersection of cryptography and psychology, password psychology is the study of what makes passwords or cryptographic keys easy to remember or guess.

Private biometrics is a form of encrypted biometrics, also called privacy-preserving biometric authentication methods, in which the biometric payload is a one-way, homomorphically encrypted feature vector that is 0.05% the size of the original biometric template and can be searched with full accuracy, speed and privacy. The feature vector's homomorphic encryption allows search and match to be conducted in polynomial time on an encrypted dataset and the search result is returned as an encrypted match. One or more computing devices may use an encrypted feature vector to verify an individual person or identify an individual in a datastore without storing, sending or receiving plaintext biometric data within or between computing devices or any other entity. The purpose of private biometrics is to allow a person to be identified or authenticated while guaranteeing individual privacy and fundamental human rights by only operating on biometric data in the encrypted space. Some private biometrics including fingerprint authentication methods, face authentication methods, and identity-matching algorithms according to bodily features. Private biometrics are constantly evolving based on the changing nature of privacy needs, identity theft, and biotechnology.

Multi-factor authentication is an electronic authentication method in which a user is granted access to a website or application only after successfully presenting two or more pieces of evidence to an authentication mechanism. MFA protects personal data—which may include personal identification or financial assets—from being accessed by an unauthorized third party that may have been able to discover, for example, a single password.

<span class="mw-page-title-main">Vein matching</span> Technique of biometric identification

Vein matching, also called vascular technology, is a technique of biometric identification through the analysis of the patterns of blood vessels visible from the surface of the skin. Though used by the Federal Bureau of Investigation and the Central Intelligence Agency, this method of identification is still in development and has not yet been universally adopted by crime labs as it is not considered as reliable as more established techniques, such as fingerprinting. However, it can be used in conjunction with existing forensic data in support of a conclusion.

IDEX Biometrics ASA is a Norwegian biometrics company, specialising in fingerprint imaging and fingerprint recognition technology. The company was founded in 1996 and is headquartered in Oslo, but its main operation is in the US, with offices in New York and Massachusetts. The company also has offices in the UK and China.

A whole new range of techniques has been developed to identify people since the 1960s from the measurement and analysis of parts of their bodies to DNA profiles. Forms of identification are used to ensure that citizens are eligible for rights to benefits and to vote without fear of impersonation while private individuals have used seals and signatures for centuries to lay claim to real and personal estate. Generally, the amount of proof of identity that is required to gain access to something is proportionate to the value of what is being sought. It is estimated that only 4% of online transactions use methods other than simple passwords. Security of systems resources generally follows a three-step process of identification, authentication and authorization. Today, a high level of trust is as critical to eCommerce transactions as it is to traditional face-to-face transactions.

<span class="mw-page-title-main">Ghana Card</span> National identity card of Ghana

The Ghana Card is the national Identity card that is issued by the Ghanaian authorities to Ghanaian citizens – both resident and non-resident, legal and permanent residents of foreign nationals. It is proof of identity, citizenship and residence of the holder. The current version is in ID1 format and biometric. It is issued by the National Identification Authority of Ghana and Regarded as a property of the country as such. In July 2023, through the initiative of the Vice President, Dr. Mahamudu Bawumia, new card numbers were issued to newborn babies as part of pilot program to incorporate newborn babies unto the database.

<span class="mw-page-title-main">Smudge attack</span> Discerning a password via screen smudges

A smudge attack is an information extraction attack that discerns the password input of a touchscreen device such as a cell phone or tablet computer from fingerprint smudges. A team of researchers at the University of Pennsylvania were the first to investigate this type of attack in 2010. An attack occurs when an unauthorized user is in possession or is nearby the device of interest. The attacker relies on detecting the oily smudges produced and left behind by the user's fingers to find the pattern or code needed to access the device and its contents. Simple cameras, lights, fingerprint powder, and image processing software can be used to capture the fingerprint deposits created when the user unlocks their device. Under proper lighting and camera settings, the finger smudges can be easily detected, and the heaviest smudges can be used to infer the most frequent input swipes or taps from the user.

Biometrics refers to the automated recognition of individuals based on their biological and behavioral characteristics, not to be confused with statistical biometrics; which is used to analyse data in the biological sciences. Biometrics for the purposes of identification may involve DNA matching, facial recognition, fingerprints, retina and iris scanning, voice analysis, handwriting, gait, and even body odor.

<span class="mw-page-title-main">Touch ID</span> Electronic fingerprint recognition feature by Apple

Touch ID is an electronic fingerprint recognition feature designed and released by Apple Inc. that allows users to unlock devices, make purchases in the various Apple digital media stores, and authenticate Apple Pay online or in apps. It can also be used to lock and unlock password-protected notes on iPhone and iPad. Touch ID was first introduced in iPhones with 2013's iPhone 5s, In 2015, Apple introduced a faster second-generation Touch ID in the iPhone 6s; a year later in 2016, it made its laptop debut in the MacBook Pro integrated on the right side of the Touch Bar. Touch ID has been used on all iPads since the iPad Air 2 was introduced in 2014. In MacBooks, each user account can have up to three fingerprints, and a total of five fingerprints across the system. Fingerprint information is stored locally in a secure enclave on the Apple A7 and later chips, not in the cloud, a design choice intended to secure fingerprint information from users or malicious attackers.

Identity-based security is a type of security that focuses on access to digital information or services based on the authenticated identity of an entity. It ensures that the users and services of these digital resources are entitled to what they receive. The most common form of identity-based security involves the login of an account with a username and password. However, recent technology has evolved into fingerprinting or facial recognition.

<span class="mw-page-title-main">Biometric device</span> Identification and authentication device

A biometric device is a security identification and authentication device. Such devices use automated methods of verifying or recognising the identity of a living person based on a physiological or behavioral characteristic. These characteristics include fingerprints, facial images, iris and voice recognition.

DeepFace is a deep learning facial recognition system created by a research group at Facebook. It identifies human faces in digital images. The program employs a nine-layer neural network with over 120 million connection weights and was trained on four million images uploaded by Facebook users. The Facebook Research team has stated that the DeepFace method reaches an accuracy of 97.35% ± 0.25% on Labeled Faces in the Wild (LFW) data set where human beings have 97.53%. This means that DeepFace is sometimes more successful than human beings. As a result of growing societal concerns Meta announced that it plans to shut down Facebook facial recognition system, deleting the face scan data of more than one billion users. This change will represent one of the largest shifts in facial recognition usage in the technology's history. Facebook planned to delete by December 2021 more than one billion facial recognition templates, which are digital scans of facial features. However, it did not plan to eliminate DeepFace which is the software that powers the facial recognition system. The company has also not ruled out incorporating facial recognition technology into future products, according to Meta spokesperson.

Biometric tokenization is the process of substituting a stored biometric template with a non-sensitive equivalent, called a token, that lacks extrinsic or exploitable meaning or value. The process combines the biometrics with public-key cryptography to enable the use of a stored biometric template for secure or strong authentication to applications or other systems without presenting the template in its original, replicable form.

<span class="mw-page-title-main">Face ID</span> Facial recognition system by Apple

Face ID is a facial recognition system designed and developed by Apple Inc. for the iPhone and iPad Pro. The system allows biometric authentication for unlocking a device, making payments, accessing sensitive data, providing detailed facial expression tracking for Animoji, as well as six degrees of freedom (6DOF) head-tracking, eye-tracking, and other features. Initially released in November 2017 with the iPhone X, it has since been updated and introduced to several new iPhone models, and all iPad Pro models.

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