2.Comp Networking - IJCNWMC - Biometric - Milind G

International Journal of Computer Networking, Wireless and Mobile Communications (IJCNWMC) ISSN 2250-1568 Vol.2, Issue 3 Sep 2012 13-26 Š TJPRC Pvt. Ltd.,

BIOMETRIC SECURITY SYSTEMS: A COMPARATIVE REVIEW MILIND GODASE1 & ANIL N. BARBOLE2 1 2

Sinhgad Institute of Management, Pune, India

Chh. Shivaji Night College of Arts & Commerce, Solapur, India

ABSTRACT The advancements in biometric technology have served as a boon in the prevention, detection and solving of crime. Increased security threats in the cities of all countries and the world have highlighted the importance of using biometric technology to prevent crime and bring perpetrators to justice. Biometric technology is becoming most important security technology in today’s IT world. This paper covers the field of Biometric Security Systems with a special focus on a comparative overview of general biometric security systems. Main objective of this paper is to provide insights on performance and comparison of different biometric security systems.

KEYWORDS: Biometrics, Feature Extraction, Biometrics Recognition System, False Reject Rate, False Accept Rate.

INTRODUCTION Biometrics is a general term used alternatively to describe a characteristic or a process. As a characteristic: a biometric is a measurable biological (anatomical and physiological) and behavioral characteristic that can be used for automated recognition. As a process: a biometric is an automated method of recognizing an individual based on measurable biological (anatomical and physiological) and behavioral characteristics. The term biometrics comes from the Greek words bios, meaning life, and metron, meaning measure. Biometrics can be defined as measurable physiological or behavioral characteristics, or both, that can be utilized to verify the identity of individuals and include fingerprint verification, hand geometry, facial recognition, iris scanning, retinal scanning, voice recognition and signature verification [1]. Biometric authentication is considered the automatic identification, or identity verification of an individual using either a biological feature they possess (physiological characteristic like a fingerprint) or something they do (behavioral characteristic, such as a signature) [2]. For authentication purposes, an individual must first be enrolled in a biometric system and the system must verify the claimed identity by comparison with a reference template [3]. In this paper Part 1 consist of the introduction of various types of biometrics systems. Part 2 gives brief comparison of the commonly used biometrics systems and their applications. Part 3 explains how biometric system works. The biometric system performance depends on the matching score is explained in part 4. The conclusion is given in part 5. At last references and bibliography are given.

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BIOMETRIC SYSTEMS First of all the term Biometrics should be defined to have an understanding of the subject. Both terms Biometrics and Biometry have been used since early in the 20th century to refer to the field of development of statistical and mathematical methods applicable to data analysis problems in the biological sciences. The following are some examples which fall under the umbrella of Biometrics as the term has been historically used:

1.

Statistical methods for the analysis of data from agricultural field experiments to compare the yields of different varieties of wheat.

2.

The analysis of data from human clinical trials evaluating the relative effectiveness of competing therapies for disease.

3.

The analysis of data from environmental studies on the effects of air or water pollution on the appearance of human disease in a region or country.

Recently the term Biometrics has also been used to refer to the emerging technology which is devoted to identify an individual on the basis of their biological traits, such as fingerprints, hand geometry, face, iris, retina, voice and hand written signatures. Each one has its strengths and weaknesses. Depending upon the application, suitable biometric system can be selected.

Finger Prints The use of biometric systems for personal authentication is a response to the rising issue of authentication and security. The most widely used method of biometric authentication is fingerprint recognition. Generally, a fingerprint is known to be unique for each person and for that reason is considered a secure method for authentication [4]. It is most widely used and less expensive. A Finger print is made of a series of ridges and furrows on the surface of the finger. Every one is known to have unique, immutable finger prints. Even the finger prints of the identical twins are different. This has 1/1000 misidentification rate means relatively high accuracy rate and is used in medium security facilities. It is affordable to scan the finger prints of a person and can be used in computer for number of applications and it gives more accuracy for currently available Fingerprint Recognition Systems for authentication [5]. The fingerprint biometric system easy to capture the data, hence it is most popular.

These are used to secure entry devices for building door locks and computer network access. These are used in banks for authorization at ATMs, credit cards. More recent application includes use of fingerprints for administering drugs and controlled substances to patients. The finger print biometric system has the following features [6]: 1.

Fairly small storage space is required for the biometric template, reducing the size of the databases required.

2.

It is one of the most developed biometrics, with more history, research and design.

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Each and every finger print including all the fingers are unique, even identical twins have different fingerprints.

4.

Relatively inexpensive and offers very high levels of accuracy.Some examples of the use of fingerprint systems in civil areas are:

5.

For fighting the abuse of civil services like social security.

6.

For permitting logins based on fingerprints.

7.

For fighting against illegal immigration.

This fingerprint recognition system is becoming affordable in a large number of applications

like Banking, Passport, Law enforcement, Civil Government, Enterprise Security, Medical and Financial transactions etc. Figure 1(a) shows a sample finger print image of a person.

Hand Geometry This biometric approach uses the geometric form of the hand for confirming an individual's identity. Specific features of a hand must be combined to assure dynamic verification, since human hands are not unique. Characteristics such as finger curves, thickness and length, the height and width of the back of the hand, the distances between joints and the overall bone structure, are usually extracted. Those characteristics are pretty much persistent and mostly do not change in a range of years. The first hand scanners were used more than 20 years ago and therefore it was one of the first biometric recognition systems. For scanning the hand a CCD (Charge-Coupled Device) camera is necessary. The camera takes two binary photos, one from above and one from beside the hand. Over 90 measurements are combined to form a template. A template is a binary file created from distinctive information from a biometric sample. Registration of a new user depends on the system but normally lasts less than 1 minute. The camera takes 3 times 2 shots and the system calculates the averages and stores the user with a special ID with his hand geometry code. The verification process requires the user to enter an ID in order to verify the claimed identity. After the user ID has been entered and the photos have been captured, the calculation of the feature set representing the biometric trait and the verification process lasts no longer than a second. Hand scan applications have proven their practical use which is shown by the 30-60% market share of biometric identification applications. The misidentification rate is 1/700 and it is used in low security buildings. The following listing should give some examples in real world areas where hand scan identification was used:

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1.

Personnel at the Olympic Games 1996 were identified with hand scans.

2.

In a lot of cases access to military plants is granted upon successful hand scan identification.

3.

Airport personnel at the San Francisco Airport are identified by hand scans.

The hand geometry recognition systems are based on a number of measurements taken from the

human hand, including its shape, size of palm, length and width of the fingers. This method is very simple and easy to use. As there is no effect of environment factors such as dry weather or dry skin, this does not appear to have dry negative effects on the authentication accuracy. Also hand geometry information may not be invariant during the growth period of the children [7]. Hand Geometry Biometric Recognition System uses the geometric shape of the hand to identify the person. This system also uses finger length, thickness, and curvature for the purpose of verification [9]. The hand geometry is not distinctive but it is the ideal choice. The hand geometry data collection is easier and hand geometry can be combined with other biometrics like finger print [8]. The recent applications of the hand geometry biometric systems include child day care centers use to verify the identity parents, payroll accuracy and access control, the fast gate pilot program to track border crossings for frequent travelers, United States military using for access control and majority of nuclear power plants in US use hand geometry for access control [10]. The hand geometry is used in biometric systems as it has the following features: 1.

Very small template size, easy to maintain and store large database.

2.

High reliability and accuracy.

3.

Robust, user friendly and easy to integrate into existing and third party systems.

4.

Ideal for rough outdoor environments like construction industry and can handle high throughput of people.

5.

Relatively inexpensive offers excellent return on investment.

6.

The hand geometry is scanned as shown in figure 1(b) and used for identification and recognition of a person.

Face The face is the commonly used biometric characteristics for person recognition. The most popular approaches to face recognition are based on shape of facial attributes, such as eyes, eyebrows,

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nose, lips, chin and the relationships of these attributes. All these attributes of the face image are shown in figure 1 (c). As this technique involves many facial elements; these systems have difficulty in matching face images [11]. The face recognition systems which are used currently impose a number of restrictions on how facial images are obtained. This face recognition system automatically detects the correct face image and is able to recognize the person. Human face detection plays an important role in applications such as video surveillance, human computer interfaces, face recognition, and face image databases [12]. To enable this biometric technology it requires having at least a video camera, PC camera or a single-image camera. Face recognition biometric systems uses facial characteristics of a person. It measures the overall facial structure, distance between eyes, nose, mouth, and jaw edges. These features are extracted and used for identification of a person [13]. Face recognition systems are used successfully in verification systems like Document control of passport, driver’s licenses, transactional authentication, credit cards, ATMs, physical access accuracy, time and attendance, entry and exit verification.

Misidentification rate is 1/100 and it can be used at low security facilities. Face recognition biometric systems are strongly recommended as it has following features: 1.

Facial photographs do not disclose the personal information.

2.

The facial image is already socially and culturally accepted internationally.

3.

It is already collected and verified to produce passports.

4.

People are aware of its capture and use for identity as well as verification purpose.

5.

It is non-intrusive.

6.

Many states have legacy database of facial images.

7.

Human verification of the biometric against the photograph/person is relatively simple and a familiar process for border control authorities.

IRIS Iris is biological feature of a human. It is a unique structure of human which remains stable over a person lifetime. The iris is the annular region of the eye. The left and right irises of an individual can be treated as separate unique identifier. A sample human eye image (iris) is given in figure 1(d). The iris information can be collected by iris image. The accuracy of iris based recognition system is promising.

Each iris is believed to be distinctive and even the irises of identical twins are also different [14]. The iris recognition system has become more users friendly and cost effective. The iris have a very low false

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accept rate as compared to other biometrics like finger print, face, hand geometry and voice. The iris image consists of the colored tissue surrounding the pupil. The iris recognition systems are known as real time, high confidence recognition of person identification [15]. The iris has a misidentification rate of 1/1,200,000 and it can be used in high-security facilities. These systems are used in many applications like passports, activation security, and controlling access to restricted areas at airports, database access and computer login, access to building and homes, border crossings and other government programme.

The iris recognition systems have following features: 1.

Perform 1: n identification with no limitation on numbers.

2.

The most robust biometric technology available in the market today never had a false acceptance.

3.

Biometric templates once captured do not need to be enrolled again, iris stable throughout a human life.

Retina Scan Along with iris recognition technology, retina scan is perhaps the most accurate and reliable biometric technology. It is also among the most difficult to use and requires well-trained, and is perceived as being moderately to highly intrusive. The users have to be cooperative and patient to achieve a proper performance. Basically the retina, a thin nerve on the back of the eye, is the part of the eye which senses light and transmits impulses through the optic nerve to the brain. Blood vessels used for biometric identification are located along the neural retina which is the outermost of the retina's four cell layers. Research has proven that the patterns of blood vessels on the back of the human eye were unique from person to person. It has even been proven that these patterns, even between identical twins, were indeed unique. This pattern also doesn't change over the course of a lifetime. Retinal scanners require the user to place their eye into some sort of device and then ask the user to look at a particular spot so that the retina can be clearly imaged. This technology involves using a low-intensity infrared light source through an optical coupler to scan the unique patterns of the retina. The reflection of the vascular information is being recorded. Retina scanning works well in both modes, identification and verification. Additional advantages include the small template size and good operational speed. It involves 360ยบ circular scan for taking 400 readings. Generally it is used for high-end security applications, primarily for physical access control. A sample human eye image (retina) is given in figure 1(e).

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Voice Various types of biometric technologies available today, voice identification and authentication solutions have a unique edge over much of the competition, because customers typically don't need to purchase new hardware to implement the solutions. Most of the voice biometric solutions can be used through a typical telephone or microphone hooked up to the computer. In order to identify or authenticate users, most voice biometric solutions create a voice print of the user, a template of the person's unique voice characteristics created when the user enrolls with the system. During enrollment the user has to select a pass phrase or repeat a sequence of numbers. The pass phrase should be in the length of 1 to 1.5 seconds. The problem with shorter pass phrases is that they have not enough data for identification.

Longer pass phrases have too much information. The user has to repeat the pass phrase or the sequence of numbers several times. This makes the enrollment process lasting much longer than with other biometric technologies. All subsequent attempts to access the system require the user has to speak, so that their live voice sample may be compared against the pre-recorded template. A voice biometric sample is a numerical model of the sound, pattern and rhythm of an individual’s voice. A problem considering the voice is that people's voices change over time along growth, or when someone has got a cold or other disease. Background noise can also be disturbing factor. The voice recognition systems have been currently used in various applications. Voice is a combination of physical and behavioral biometrics. The figure 1 (f) shows a sample speech signal. The features of person voice are based on the vocal tracts, mouth, nasal activities and lips movement that are used for synthesis of sound. These physical characteristics of human speech are invariant for individuals. The behavioral part of the speech of person changes over time due to age, medical conditions, and emotional state. The speaker dependent voice recognition systems are text dependent; and the speaker independent systems are what he or she speaks [16]. The speaker dependent voice recognition system is more difficult to design but provides more protection. The speech recognition is most important research area in the today’s world. There are various speech recognition approaches; among those are the acoustics phonetic pattern comparisons and automatic speech recognition approach [17]. The performance of speech recognition system depends on various factors some of them are speaker variation, ambient noise, and variation in the tone of the same speaker, sensitivity of phonetic input systems, distance and regular variations. The speaker recognition is most appropriate in phone based applications, the entertainment TV channels [16]. Banks are starting to use this technology, instead of dialing in a pin number you would speak and the computer would recognize your voice. It has misidentification rate 1/30 and can be used in low security facilities. Voice

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recognition biometric systems are used for access control, banking, government offices and entertainment applications, smart cards, PIN and other security purposes.

Signature Signature verification is the process used to recognize an individual's hand-written signature.

Dynamic signature verification uses behavioral biometrics of a hand written signature to confirm the identity of a person. This can be achieved by analyzing the shape, speed, stroke, pen pressure and timing information during the act of signing. On the other hand there is the simple signature comparison which only takes into account what the signature looks like. So with dynamic signature verification, it is not the shape or look of the signature that is meaningful, it is the changes in speed, pressure and timing that occur during the act of signing, thus making it virtually impossible to duplicate those features. Devices which enable dynamic signature verification store the behavioral factors and the captured signature image itself for future comparison in their database. These devices account changes in one's signature over time by recording the time and the dynamic features each time a person uses the system. The major difficulty with this technology is to differentiate between the consistent parts of a signature; these are the characteristics of the static image, and the behavioral parts of a signature, which vary with each signing.

Comparing many signatures made by one individual reveals the fact that an individual’s signature is never entirely the same and can vary substantially over an individual's lifetime. Allowing these variations in the system, while providing the best protection against forgery is a big problem faced by this biometric technology. Functions are provided to capture that handwriting, extract the relevant features, and compare two different samples. It has misidentification rate1/100 and can be used in low security facilities. The financial industry sometimes uses signature verification for money transactions. The Manhattan Bank was the first bank to test such an approach by using a biometric signature application for their money transaction system. The figure 1 (g) shows a sample signature.

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Comparison of Biometric Systems The biometric systems such as fingerprint, hand geometry, face, iris, retina, and Signature have compared based upon factors such as accuracy, ease of use and user acceptance. These factors are different for each biometric type. These can be measured in High (H), Medium (M) and Low (L) [18].

Table 1 compares the biometric systems based on different factors.

BIOMETRIC RECOGNITION SYSTEM Biometric Recognition Systems are used to identify an individual person based on the feature vectors of any one of the biometric that the person possesses [19]. These systems are person authorized systems hence offer more secure and convenient process of identification compared to alternative methods of identification. The computer based security systems are used in various commercial, civilian and forensic applications. Each person has to establish the identity ranging from drivers’ license to gaining entry into a country to the passport. The biometric system uses the individual’s physical characteristics like fingerprint, hand geometry, face, voice or iris. They are more reliable and secure as they provides the access to authorized users in their physical presence [20]. Looking at biometric systems in a more general way will reveal certain things all biometric-based authentication systems have in common. In general such systems work in two modes:

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Enrollment Mode: In which biometric user data is acquired. This is mostly done with some type of biometric reader. Afterwards the gathered information is stored in a database where it is labeled with a user identity (e.g. id number, name) to facilitate authentication [21].

Authentication Mode: Again biometric user data is acquired first and used by the system to either verify the users claimed identity or to identify who the user is. While identification involves the process of comparing the user’s biometric data against all users in the database, the process of verification compares the biometric data against only those entries in the database which are corresponding to the users claimed identity.

In general one can consider the verification of the identity of a person a two-class problem: •

either the person is who he/she claims to be (client)

•

or the person fails to be the one he/she claims to be (impostor)

A simple biometric system consists of four modules: 1.

Sensor Module: This module acquires biometric user data. Examples of sensor module would be a retina scanner or a fingerprint sensor.

2.

Feature Extraction Module: This module is responsible for extracting feature values of a biometric trait. If hand geometry would be used as a biometric trait then feature values would include width of fingers at various locations, width of the palm, thickness of the palm, length of fingers etc.

3.

Matching Module: The matching module compares the acquired biometric features against those stored in a database.

4.

Decision-Making Module: The user’s identity is either established or a claimed identity is accepted or rejected.

This is done based on the results of the matching modules. Since we are dealing with a binary

decision scheme it is obvious that the decision-making module can make two kinds of errors. The errors, which can be made in the process of verification, are called: •

False Rejection (FR): when an actual client gets identified as an impostor.

•

False Acceptance (FA): when an actual impostor gets identified as a client.

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BIOMETRIC SYSTEM PERFORMANCE EVALUATION The performance of a biometric system can be measured as the False Rejection Rate FRR equation (1) or the False Acceptance Rate FAR equation (2), which are defined as:

A perfect biometric recognition system would have a FRR = 0 and a FAR = 0 which is a little bit unachievable in reality. It is also interesting that any of the two values FRR and FAR can be reduced to an arbitrary small number, with the drawback of increasing the other value. Another interesting value is the Total Error Rate TER equation (3) which is defined as:

At this point it is important to emphasize the fact that these measures could be heavily biased by one or either type of errors (FAR or FRR) depending only on the number of accesses which have been used in obtaining these respective errors. This means that the TER will always be closer to that type of error which has been obtained with the largest number of accesses. The overall performance of a biometric recognition system should not be measured by the TER but rather by the Receiver Operation Characteristic ROC, which represents the FAR as a function of the FRR. So wherever there is a tradeoff of error types, a single performance number is inadequate to represent the capabilities of a system. Such a system has many operating points and is best represented by a performance curve. The ROC curve has been used for this purpose. Generally false alarm is plotted on the horizontal axis whereas the correct detection rate is plotted on the vertical axis.

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In some applications though the Detection Error Tradeoff DET curve has been found to be more useful since both types of errors are plotted on the DET curve. Typically one can observe approximately straight lines, which do correspond to normal likelihood distributions, in DET plots. This method is especially useful in speech applications [22]. Some high security applications tend to keep the FAR as small as possible when they operate at the point on the ROC. Forensic science operates with a very low FRR and a very high FAR since they desire to catch a criminal even at the expense of examining large numbers of false accepts. Civil applications try to work at a level where FRR and FAR are both as low as possible see Figure 3.

The recognition accuracy is depending on the image acquisition, the position of acquiring sensor, intensity of light focusing, environmental changes, noise, and bad user’s interaction with the sensor. Therefore the two images acquired by the sensor may not be having same characteristics [23].

The biometric matching systems are used to find the matching score between the two images. The threshold t is assumed and the matching score is less than t then the image is considered as the different person [15]. Then two errors are measured in terms of False Acceptance Rate FAR and False Rejection Rate FRR. FAR: The biometric measurement between two persons is same. FRR: The biometric measurement between two persons is different. If the system decreases t to make the system more

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tolerant to input variation and noise, FAR increases. On the other hand if the system increases t to make the system more secure, FRR increases accordingly [19]. Figure 4 shows the performance of the system which is depending on the matching score between two images and is measured by the errors; False Acceptance Rate FAR and False Rejection Rate FRR.

CONCLUSIONS Biometrics is an essential component of any identity-based system, but they themselves are vulnerable. Some of these attacks are simple to execute; solutions to these attacks have been identified, but there is still room for improvement. Attacks on biometric systems can result in loss of privacy and monetary damage, so the users need to be convinced about the system protection. New security issues with biometric systems may arise as their use becomes more widespread. In spite of this, biometric systems are being deployed for securing international borders, controlling access and eliminating identity theft.

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