Biometrics for ensure Cybersecurity
A brief Introduction to Biometrics
The words “bio (Greek work)” and “metrics,” where bio stands for “life” and “metrics” denotes measurements, are combined to form the phrase “biometrics.” Due to their high degree of accuracy in identifying an individual, biometrics are frequently utilized for security purposes.
A person can be recognized or authenticated using their physiological traits thanks to biometrics. These traits must be instantly discernible and verified.
The benefit of using biometric authentication is that it can verify the user’s unique traits. These traits can be physical ones such as fingerprints, face, and iris, or behavioral ones such as voice, handwritten signature, and keyboard tapping.
History of Biometrics
The use of biometrics is not new in this world. The face is one of the earliest and most fundamental instances of a trait that people use for identification. Faces have been used by humans to distinguish between known (familiar) and unknown (unfamiliar) people ever since the beginning of civilization. This simple task became increasingly challenging as the population increased.
Alphonse Bertillon, a scientist, developed a system in the 19th century for identifying people by taking measurements of their bodies. Height, the length of one foot, an arm, and the index finger were all measured while the individual was photographed. He had admitted that while other physical qualities, like weight, hair length, etc., fluctuate over time, other aspects of the human body, like the length of the fingers, remain constant. The same-sized individuals would be mistakenly considered as one, making this strategy soon unpopular. Consequently, Richard Edward Henry, a scientist from Scotland, developed a novel fingerprinting technique with the aid of this research.
In 1935, Dr. Carleton Simon and Isadore Goldstein made the initial mention of retinal identification. In 1971, the first facial recognition article was published (Goldstein et al.). In 1976, Eye Densify Inc. began investing in research and development. In 1981, the first scanning retina system for use in the industry was created.
The Iris identification technology was introduced by John Daugman in 1993.
In 2000, the FBI implemented IAFIS, which has a database of around 47 million prints, an average of 50,000 searches daily, a 15% search rate in lights-out mode, and a 2-hour criminal search response time.
The Biometrics Automated Toolset (BAT) was introduced in 2001, offering an accurate identification method.
The ability to identify people using their biometrics is now a reality, and biometric access control systems will soon replace traditional access control procedures to protect sensitive data. The benefit of using biometric access control over conventional password protection is that it takes a
long time to retrieve a lost password, whereas password-secured systems are easier to intercept. In addition to being used for access control, biometrics are also used for tracking attendance.
The use of biometric authentication methods is expanding across consumer and enterprise platforms, while systems that demand higher standards of security and dependability are being filled in by new forms of fraud prevention and enhanced biometric procedures.
Biometrics security
A type of security known as “biometric security” uses a person’s behavioral and physical features to confirm their identity. It is the most reliable and powerful physical security method for confirming identities.
According to biometric authentication, people can be recognized precisely based on their innate behavioral or physical traits.
Biometrics authentication
Authentication: verifying the identity of a user, process, or device, often as a prerequisite to allowing access to resources in an information system.
Biometric authentication is a cybersecurity process that verifies a user’s identity using their unique biological characteristics as their password.
Types of biometric authentications
Iris recognition: Iris scanning, commonly referred to as "iris recognition," is the method of employing visible and near-infrared light to take a high-contrast image of a person’s iris.
Facial recognition: Facial recognition is a technique for identifying or verifying someone’s identity using their face. Facial recognition technology allows for the identification of individuals in still photos and videos as well as in real-time.
Fingerprint recognition: fingerprint recognition is an automated method of confirming or identifying a person based on the comparison of two fingerprints. When compared to other biometrics, fingerprint recognition is particularly popular due to ease of acquisition, established use, and acceptance. Among all the biometrics, Fingerprint-based identification is the earliest biometric approach and has been used successfully in a wide
range of applications for more than a century. The second biometric to be used in the ePassport is optional, although starting in the middle of 2009, it will be required in Europe.
DNA matching: An individual’s genome, or DNA, is distinct and is regarded as private or personal information since it contains details about their family and ancestry.
Voice recognition: Computers can comprehend human speech thanks to a capability in their hardware or software. Without using a keyboard, mouse, or button presses, voice recognition software is widely used to control a device, issue commands, or write.
Typing recognition: When someone types on a computer keyboard, a person’s precise timing information about when each key was hit and released is referred to as typing dynamics, typing biometrics, keystroke dynamics, and type dynamics.
Recent Biometrics Development
○ Multi-biometrics: The primary goal of biometric systems is always verification or identification accuracy. Unibiometric systems, or biometric systems that only use one biometric trait, typically have some
drawbacks and are unable to deliver adequate recognition performance.
The performance and reliability of the biometric system can be improved with the help of multi-biometric systems, which combine data from many biometric qualities.
A multi-biometric system combines data from various biometric qualities to overcome the limits of any single biometric system. The three levels of fusion are feature level, matching score level, and decision level.
○ 3D Biometrics: Biometrics recognition has been expanding quickly, and In a range of applications, many biometrics systems have been widely deployed. However, most biometric recognition methods rely on 1D signals or 2D pictures. The current state of 1D and 2D biometrics technology has
significant drawbacks
•If a person has diabetes, it affects their eyes, which causes variations that make it difficult to recognize their iris.
•If the person’s fingertip is dirty or the finger is twisted when taking the fingerprint, the print may be deformed, unreadable, or unidentified.
•It has been observed that a person’s voice changes with age. Additionally, this approach might not verify properly if the person’s voice alters due to the flu or a throat ailment or if there is too much background noise.
•A quick and reliable way for personal authentication is the traditional 2D palmprint recognition, however, 2D palmprint photos are easily forged.
The most recent development in this field of research is 3D biometric technologies. A few commercially available tools, such as the Konica Minolta Vivid 9i/910, and Cyberware's whole body color 3D scanner can capture an object’s three-dimensional information. These professional 3D scanners may be used to acquire 3D biometric information and are very quick and accurate.
○ Multispectral Biometrics: Some essential qualities of a biometric system include adaptability, usability, and security. Such a system must be able to collect and process biometric data at all hours of the day and night,
regardless of the weather or environmental conditions, and must be impervious to spoofing attempts. One of the few methods that have been demonstrated to address several of the problems is multispectral biometrics. The visible spectrum and beyond can both be simultaneously imaged using multispectral imaging. Information from various electromagnetic spectrum bands has been widely analyzed in the fields of remote sensing, medical imaging, and computed vision.
