Methods of Biometric Authentication - facial reader scanner biometric mask protect
Authentication methods include verifying the identity of an individual.
Verification is usually obtained by personally showing what he knows, what he has, or what he is.
The most traditional form of authentication depends on the individual who provides the username and password, thus showing some things that the user knows.
Due to the failure of the traditional authentication methods, biometric authentication methods are becoming more and more popular.
Using dictionary attacks or rainbow tables, a combination of username and password can be vulnerable.
Biometric authentication methods do not generate a hash of user input, which makes it almost impossible to capture and decode user input.
Biometric authentication depends on what proves the individual, not what the individual knows.
This makes biometric authentication less vulnerable to replication attacks than traditional authentication methods.
There are basically three kinds of biometrics, including physical biometrics, behavioral biometrics and cognitive biometrics.
The most common thing so far is physical biometrics.
Most listed physical biometric systems scan individuals in some way to differentiate features.
These scans basically create images of a personal fingerprint, hand, face, iris, or retina (commercial reference, 2011 ).
Physical biometric scanners account for about 86% of the biometric market.
Iris scanning measures the most stable individual features, as the iris pattern of the individual does not change with birth time.
However, Iris and retina scans require the individual's eyes to be very close to the scanner, so people tend to choose other methods.
This may explain why Iris and retina scanners do not exceed the market.
Regardless of which type of physical features the biometric system measures, the final result is to create a template that authorizes individual biological features through computer analysis scans.
The template is a very large alphanumeric key that was created when a personal registration system was created.
A future authentication scan is then compared to the template and access is granted or denied based on how well the future scan matches the template (Business Reference, 2011 ).
Behavioral biometric authentication relies on measuring an individual's voice pattern, signature feature, or typing style.
Behavioral biometrics effectively replaces what you do for yourself.
Electronic payment week on Page 20051).
The voice mode can be easily captured and is unique between individuals.
One problem with using voice mode is that background noise may affect an individual's attempt to authenticate to the system and create a false negative or block an individual who should be granted access.
Since there is no background noise problem, typing features and signature dynamics are more reliable than speech recognition.
Typing features measure the way a person types.
The measurement is characterized by dwell time and flight time when typing a specific phrase.
Dwell time is the amount of time the user's finger stays on a specific key, while typing and flight time are the amount of time the user spends moving between keys.
When the user sets up the account, the user is prompted to type a specific phrase multiple times.
When a user types a specific phrase, the system measures the user's features.
The user then types the same phrase on authentication.
Signature-based dynamic biometric authentication works in a similar way.
The new user can sign his or her signature several times and the system will measure pen pressure and pen speed, so it is not possible for this signature to be forged in terms of the authentication system (Electronic Payment Week, page 20051).
This authentication method is simple for the user and provides a reasonable amount of certainty as to who the user claims to be, because the signature must not only match the individual signature, it must also match the signature and must be signed in the same way.
Cognitive biometrics is relatively new for biometric authentication.
The simple form of cognitive biometric authentication leads individuals to relate to things of the past.
The security of some forms of Internet access depends on this form of cognitive biometric authentication, which leads to the thinking of users.
However, this simple form of cognitive biometrics has some same problems as password authentication;
Shoulder surfers can look at a person to answer questions and then copy them in the future.
Biological determination of Avalon (n. d.
) A more complex form of cognitive biometrics is proposed, which grants a patent for the interface between the individual brain and the machine to measure the cognitive response to the task.
In response to a set intelligent task, a pattern of blood flow velocity changes is obtained, which is used to form a repeatable "mental feature" in automation personnel"
Machine interface system.
The system is designed to go beyond passive recognition, but to set the desired level of "mental performance" before entering the system.
(Biological determination of Avalon, n. d. ).
This form of cognitive biological features creates a signature based on an individual's mode of thinking, which may be the most difficult pattern to replicate.
Concerns about unentity fingers used to circumvent fingerprint scanners are common in the early days of biometrics and remain a concern today, although technology has improved significantly since the early days.
Adding a temperature sensor to the fingerprint scanner can help prevent cold fingers from being used for access.
Bayly, Castro, Arakala, Jeffers, and Horadam (2010) mention the possibility of a fake biometric technique like Gumi fingerprints that an attacker can present a mask or pre-recorded sound on the sensor of the system69).
These possibilities require manufacturers to include mechanisms to ensure that the biometric certificate originates from the presenter.
The establishment of public confidence in biometric authentication methods has brought serious problems to the biometric authentication system industry.
Charndra and Calderor (2005) address concerns of active groups that claim that biometrics are invasive and provide for a greater reduction in personal privacy and freedom.
Unlike traditional identifiers such as passwords and tokens, biometrics are inextricably linked to a specific person and cannot be changed, replaced or modified104).
In today's time, individuals seem more likely to exchange some privacy for security, but the possibility of this trend continuing is problematic.
The last personal concern about biometrics concerns the central repository used by the system.
The electronic payment Week (2005) indicates that these repositories may be invaded by intruders.
Such behavior will destroy enterprises and individuals;
Get all their assets stolen from all their accounts, not just from one account1).
The effectiveness of the biometric system is related to the ability of the system to distinguish a given population sample.
Biometrics did not provide an indisputable decision.
Charndra and Calderor (2005) indicate that the literature defines biometrics as identifiable (not unique) physiological and behavioral features that can be used for identification and certification195).
The definition states that when a biometric sample matches a template, the identity is considered a possible match, not an indisputable identification.
There are two stages of biological certification.
The first phase is registration when an individual registers with the system and creates a biometric template.
The second phase is validation when a person presents a biometric scan to compare with the template.
In both stages, individuals may experience scanning problems.
DigitalPersona has launched a fingerprint scanner, which the company claims has a registration success rate of 90% and a verification success rate of 100%.
This means that 10% of the population will have problems registering in the system.
Jain and Ross (2004) claim to use a multi-biometric system with multiple biometric scans to increase the likelihood that a possible match is actually a valid identity by matching multiple features.
These systems also reduce the likelihood that one person will successfully cheat another person's identity.
An intruder trying to use a finger model also needs to replicate another feature, such as the writing dynamics of the victim.
Charndra and Calderor (2005) indicate that another limitation on the effectiveness of biometric devices is the extent to which these devices can perform possible matches after natural occurrence, such as aging.
As the age grows, the physical features of the elderly change, and even if these changes occur, the biometric device must be able to match the template with the sample.
Similar situations occur after certain types of surgery that change the appearance or cause an accident that causes limb loss.
An alternative to biometric systems that are unable to adapt to these changes is to require subjects to re-register the system after these changes occur, which will increase the cost of ownership.
The most common hardware-based biometric systems include fingerprint scanners and iris scanners.
Software biometric systems include systems that measure typing dynamics and signature features.
The cost of implementing these systems depends on the type of system, the location of the system, and the number of users.
Digital role in Americaare U. (Grotta, 2001).
A security enhancement of the model is the device's ability to encrypt images when they are acquired.
Other devices sent to the United Nations
Encrypt the image to the connected computer and ask the computer to encrypt the image.
In order to prevent tampering, confidential should require encryption of the image before transmission.
A fingerprint scanner like this is a good choice for physical access control mechanisms.
Biometric protection against unauthorized access to desktop computers has traditionally been done using fingerprint scanners, as mentioned above.
These scanners can be costly to a large extent.
This is designed for desktop authentication. U. are U.
The decline in desktop computer costs, coupled with the low cost of this iris recognition technology, should make desktop certification for each major company more important.
Now, Web access can be economically protected using software-based typing dynamics and BioPassword 4.
From NetNanny, connect unique physical features to an individual's network account to provide a positive user identity.
BioPassword links specific typing styles and patterns to the user's password for a flexible and secure solution (Monro, 2001 ).
Net Nanny provides a tiered pricing structure for the software, with prices ranging from $100 to $50
4,000 the user license for the user license is $40.
The secrecy, integrity and availability of the organization's information assets are no longer adequately protected.
Passwords are easily cracked by violence.
The method of force is still simple through observation.
In order to provide adequate protection for information assets and systems, another form of certification is required.
Biometric authentication methods are replacing traditional authentication methods to provide more adequate protection.
There are three kinds of biometric authentication: physical biometric identification, behavioral biometric identification and cognitive biometric identification.
In the case of physical biometrics;
In the case of behavioral or cognitive biometrics.
While biometric authentication systems can effectively provide better protection for information systems, there are also some effective concerns that have slowed down the entire
Promotion and implementation of these systems.
These issues include the possibility that biometric authentication systems may allow unauthorized access to the system, or that a central repository of biometric templates may be compromised.
However, improvements in technology and the introduction of multi-biometric systems are gradually leading the public to embrace the technology.
The cost of implementing a biometric authentication system depends on many variables, such as the location of the device and the number of users.
However, what matches the goods is
Like the cost of a desktop computer, biometric authentication systems are becoming more affordable for organizations of all sizes.
The low cost of protecting information systems and network transactions using biometric authentication methods should motivate the implementation of such a solution. Bayly, D. , Castro, M. , Arakala, A. , Jeffers, J. , & Horadam, K. (2010).
Fractional biometrics: protect privacy in biometric applications. (1), 69-82. doi:10. 1007/s10207-009-0096-Chandra, A. Carl Delo, T. (2005).
The challenges and limitations of biometric diffusion in information systems. (12), 101-106.
Retrieve from EBSCOhost. Jain, A. K. , & Ross, A. (2004).
Multi-biometric system(1), 34-40.