Liveness Taxonomy

In liveness taxonomy, Adversarial Spoofing Attacks (AXs) refer to a malicious technique, in which spoofing data is presented as genuine to the authentication system. This type of attack exploits the lack of robustness in a Deep Neural Network (DNN), which is responsible for

Essentially, biometric spoofing combines two elements: a) Production and b) Presentation. The production stage implies creation of a synthetic artifact that imitates a certain biometric trait such as voice, face, fingerprint, eye retina, etc. The presentation stage includes direct

In biometric security, an injection attack is a type of indirect attack, in which a bona fide biometric trait is digitally replicated and presented to a security system on the internal, software level. This in turn tricks a recognition system into making a specific decision. (Although

In liveness taxonomy, Presentation Attacks (PA) is a demonstration of a certain physiological trait — fingerprint, face, voice — that is aimed at bypassing a biometric security system. Numerous sources also use the spoofing term to describe the issue. These attacks are

Liveness detection is a capability of a biometric system to differentiate falsified biometric traits presented to its sensors from the genuine ones. Liveness detection is, perchance, the central component in biometric security as it prevents fraudulent enrollment attempted with

In liveness taxonomy, keystroke dynamics recognition (KDR) is based on identifying tempo, rhythms and manner of keyboard typing that is intrinsic to a specific individual. The concept can be traced back to the 19th century when telegraphy first appeared. It was relatively

Spoofing detection solutions based on biometric recognition and authentication should meet a set of criteria. Typically, the following standards must be observed: Accuracy. Algorithms employed in a state-of-the-art system should provide high accuracy and the lowest possible

Remote identity proofing (RIDP) and protocols similar to Know Your Client (KYC) invoked the need for laws and initiatives that would standardize the procedure of verifying a person’s identity in online transactions. One of the best-known initiatives is the eIDAS Regulation established

Biometric liveness detection is a necessary component in modern verification systems. However, use of biometric verification in home-grade devices (Internet of Things) and smartphones has led to an increase in biometric spoofing, which is carried out via numerous

IP spoofing is a type of cyberattack, which disguises harmful or decoy websites as trusted platforms for fraudulent and harmful purposes. These purposes include phishing private data, stealing digital or physical assets, and sabotaging online entities. IP antispoofing is a

Multimodal liveness detection — as opposed to unimodal approach — is based on the principle of scanning and analyzing more than one biometric features of a person. Currently, most detection solutions focus on a single parameter: voice, iris, fingerprints, face, hand geometry

In liveness taxonomy, fingerprint liveness is a security technique, which serves to deny system access to Presentation Attacks (PAs) performed with a fingerprint replica of a legitimate user. Fingerprint recognition technology was initially developed in 1975 at NIST, where scanners

Document liveness detection refers to the verification that a document presented remotely is authentic and real. This is necessary to verify people, detect forgeries, as well as prevent potential digital crime. There are various types of fraud that involve fake document usage

Remote identity proofing (RIDP) is a procedure that allows a person to digitally prove that he/she is who they claim to be (“natural person” in liveness classification) via a specific online service. Such a proofing can be performed with the help of a mobile gadget or web camera

Remote identity proofing (RIDP) is a procedure of collecting and processing information regarding someone’s identity online. It is vital for digital onboarding, Know Your Client compliance, and other online services. RIDP greatly depends on analyzing biometric data

Remote KYC is based on creating a costumer’s profile to establish, verify and confirm their identity based on biometric standards, liveness taxonomy, etc. Requirements for this profile may vary for different companies/organizations. Typically, they include customer information such

Performance metrics and liveness standards play an important role in the testing of biometric systems. They help to reveal error rates, execute a full-scale security test and eradicate possible vulnerabilities. Common errors in a biometric system occur when a detection system fails to

Internet of Things or IoT is a technology that interconnects physical objects and systems by embedding sensors, software and data exchange capabilities in them. The first IoT device was introduced in the 1980s, when a group of students at Carnegie Melon University “taught” a

In liveness taxonomy, Liveness Detection (or biometric anti-spoofing, or biometric liveness) is a set of preventive measures, which ensure that original or mimicked biometric authorization data cannot be used by impostors for purposes of theft or fraud. Anti-spoofing and liveness