Biometric Authentication And Security Features Influencing Smartphone Sales Statistics.

Biometric Authentication And Security Features Influencing Smartphone Sales Statistics. – Department of Care Tasks in Family Care Systems: A Comparative Analysis of Gender Inequality and Socio-Economic Differences in Austria and Slovenia

Exploring lean management methods used in shared service centres, drivers and barriers to selecting processes for improvement in light of risk management and environmental, social and governance (ESG) reporting

Biometric Authentication And Security Features Influencing Smartphone Sales Statistics.

Biometric Authentication And Security Features Influencing Smartphone Sales Statistics.

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Biometric Authentication And Security Features Influencing Smartphone Sales Statistics.

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Biometric Authentication And Security Features Influencing Smartphone Sales Statistics.

Pdf) Security Issues Of Internet Based Biometric Authentication Systems: Risks Of Man In The Middle And Biophishing On The Example Of Biowebauth

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Biometric Authentication And Security Features Influencing Smartphone Sales Statistics.

Received: April 15, 2022 / Revised: July 9, 2022 / Accepted: July 13, 2022 / Published: August 1, 2022

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This paper provides an analysis of innovations in the biometrics market, which are beginning to play a very important role in personal identification and identification systems. The aim of the study was to analyze current habits and opinions regarding payment methods, as well as to identify risks and opportunities for new biometric solutions in this area. First, the history of the biometrics market is presented. Patterns of acceptance of new technologies are explored and modified. The authors used literature reviews, qualitative research (focus groups), and quantitative research (questionnaire surveys) as methods. The main value and importance of biometrics is the uniqueness of biometric patterns (e.g., face, fingerprint, iris, etc.), which takes the security of these systems to a new level. The results of the quantitative study based on the qualitative survey show positive verification of the hypothesized reasons; For example, it is important that the age of potential users of biometric payments influences concerns about personal data. The fear of losing personal data affects the perceived security of biometric payments. Perceived security has a very strong influence on attitude toward biometric payments, and is the strongest predictor of behavioral intention to use biometric payments.

Biometric Authentication And Security Features Influencing Smartphone Sales Statistics.

Biometrics is a field that deals with measuring the characteristics of living organisms, including humans of course, but also animals and plants. Based on the application of biometrics in the field of authentication and identification lies a number of characteristics of living organisms, which allow a clear differentiation between an individual and a population. When choosing a particular biometric feature, we should be guided by the following criteria:

Biometric traits can be divided into physical/physiological and behavioral traits. Physiological traits are related to the structure of individual body parts, for example, the pattern of the iris, the shape of the hand or ear, the fingerprint, the geometry of the face, or the shape of our veins. Behavioral traits are developed and established during a person’s maturation process and are linked to their behavior, for example, the way they walk, and their P300 brain wave (because brain waves have proven to be unique enough to be used as biometrics in individuals). their handwritten signature (keystrokes), or their vocal characteristics (although the dual nature of these biometrics is sometimes pointed out). An example of a combination of both types of features can be found in Figure 1.

Biometric Authentication And Security Features Influencing Smartphone Sales Statistics.

The Smartphone Multiplier Effect

Biometric security in the modern sense was born in the nineteenth century, thanks to the innovations of French administrators, anthropologists, and investigators [2]. The first known research publication on automatic biometric recognition was Michel Trarring’s 1963 paper [3] in the journal Nature on fingerprint matching. Automated biometric systems based on other features such as voice, face, and handwriting also began to be developed in the 1960s. Later, biometric systems were developed based on features such as hand and iris geometry. In this sense, it has been almost 70 years since the first research paper on automatic biometric recognition was published [4]. Figure 2 is a timeline of fingerprint development. Other biometric traits were investigated in the 19th century in a very similar time frame.

Each biometric feature has its own advantages, disadvantages, and limitations, which should be considered when selecting it for a particular use case. Due to the above-mentioned characteristics of biometric features, especially uniqueness, time unreliability and ambiguity, they are considered sensitive data and must be protected at multiple levels. The theft of raw biometric data could be used by an adversary to impersonate the victim and lead to unauthorized access or theft. The European Union, in its General Data Protection Regulation (GDPR), addresses this issue and defines biometric data as particularly sensitive and assigns them the need for special protection [5]. In light of the above, special attention should be paid to primary biometric data, which primarily means reducing its processing to a minimum. The basic solution to this problem is to use so-called one-way processing [6], which generates a template/profile/code from a sample of raw biometric data that represents a fingerprint of that data. This code still has individual characteristics and can be compared with others, so the idea of ​​using biometrics is preserved. However, it is not possible to reconstruct the original biometric data based on this alone. This approach also protects the user in the event of a code database leak, since its use in transformed form is trivial – as is the case with password hashes. An example of iris coding according to Dogman’s solution [7] can be found in Figure 3.

Biometric Authentication And Security Features Influencing Smartphone Sales Statistics.

Referring to palm prints, biometric template protection methods, such as revocable biometrics and biometric encryption systems, are required to avoid direct detection of original fingerprint features [8]. To enhance user security, an approach based on so-called revocable biometrics can also be used in different types of biometrics [9]. This solution is based on the ability to create multiple biometric identities from a single source data and manage these identities. In some cases, we may delete a certain biometric identity and create another one based on its raw data. Such an application could be particularly useful when the system database in which an identity was used has been leaked or when we have reasonable suspicion that someone is trying to impersonate that identity. When using a revocable biometrics approach, we typically need an additional source of external information beyond biometrics so that we can modify the identity accordingly and link it to the biometric data. This information may, for example, be a string of characters entered by the user, such as a password or personal identification number (PIN). Another existing method for template protection (used in fingerprint biometrics) is the fingerprint cryptosystem, which is a fusion of biometrics and cryptography, which attempts to popularize biometrics as a authenticator for cryptographic applications, where biometric features are claimed to be secure [8].

Pdf) Authentication Of Smartphone Users Using Behavioral Biometrics

No matter how much effort goes into securing biometric data, at some point an adversary will be able to grab it and try to use it to impersonate a legitimate user. This type of action is called a display attack and the defense is display attack detection (PAD).

Biometric Authentication And Security Features Influencing Smartphone Sales Statistics.

To combat these forgery attempts, vitality tests are used [10], which are the basis of biometric applications. Figure 4 shows a general diagram of how a biometrics-based security system works. Viability tests are designed to detect attempts to substitute synthetic objects – imitating real biometric features, including stolen biometrics converted into fake samples – photos, masks, recordings, etc. Any biometrics-based security system should focus heavily on liveness testing and implementing high detection of surrogate attacks. However, this is not an easy task because adversaries have increasingly sophisticated fraud methods at their disposal and are often very determined to point out weaknesses in the system.

Some of the above applications have already been addressed and will be described in more detail later in this article. However, we now want to focus on the last two applications that undeniably distinguish biometrics from other security solutions.

Biometric Authentication And Security Features Influencing Smartphone Sales Statistics.

How To Keep Security For Apps. How Do You Secure Your Mobile…

Biometrics, as opposed to standard authentication

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