Presenting fake biometrics at the sensor: In this mode of attack, a possible reproduction of the biometric feature is presented as input to the system. Examples include a fake finger, a copy of a signature, or a facemask. Resubmitting previously stored digitized biometrics signals: In this mode of attack, a recorded signal is replayed to the system, bypassing the sensor. Examples include the presentation of an old copy of a fingerprint image or the presentation of a previously recorded audio signal.
Overriding the feature extraction process: The feature extractor is attacked using a Trojan horse, so that it produces feature sets preselected by the intruder. Tampering with the biometric feature representation: The features extracted from the input signal are replaced with a different, fraudulent feature set assuming the representation method is known.
Often the two stages of feature extraction and matcher are inseparable and this mode of attack is extremely difficult. However, if minutiae are transmitted to a remote matcher say, over the Internet this threat is very real.
Corrupting the matcher: The matcher is attacked and corrupted so that it produces preselected match scores. Tampering with stored templates: The database of stored templates could be either local or remote. The data might be distributed over several servers. Here the attacker could try to modify one or more templates in the database, which could result either in authorizing a fraudulent individual or denying service to the persons associated with the corrupted template.
A smart card-based authentication system,where the template is stored in the smart card and presented to the authentication system, is particularly vulnerable to this type of attack. Attacking the channel between the stored templates and the matcher: The stored templates are sent to the matcher through a communication channel. The data traveling through this channel could be intercepted and modified.
Overriding the final decision: If the final match decision can be overridden by the hacker, then the authentication system has been disabled. Even if the actual pattern recognition framework has excellent performance characteristics, it has been rendered useless by the simple exercise of overriding the match result. There exist several security techniques to thwart attacks at these various points. For instance, finger conductivity or fingerprint pulse at the sensor can stop simple attacks at point 1.
Encrypted communication channelscan eliminate at least remote attacks at point 4. However, even if the hacker cannot penetrate the feature extraction module, the system is still vulnerable. The simplest way to stop attacks at points 5, 6, and 7 is to have the matcher and the database reside at a secure location.
Of course, even this cannot prevent attacks in which there is collusion. Use of cryptographyprevents attacks at point 8. It is observed that the threats outlined in Figure are quite similar to the threats to password-based authentication systems. For instance, all the channel attacks are similar. However, in an automated biometric-based authentication system, one can check the liveness of the entity originating the input signal.
Depending of where the biometrics is deployed, the applications can be categorized in the following five main groups: forensic, government, commercial, health-care and traveling and immigration. In particular, the AFIS automatic fingerprint identification system has been used for this purpose. Lately the facial-scan technology mug shots is being also used for identification of suspects.
Another possible application is the verification of persons of home arrest, a voice-scan is an attractive solution for this problem. The typical application are: Identification of criminals- collecting the evidence in the scene of crime e.
Surveillance --using cameras one can monitor the very busy places such as stadiums, airports, meetings, etc. Looking in the crowds for suspect, based on the face recognition biometric, using a images e. Since the events of September 11, , the interest in biometric surveillance has increased dramatically, especially for air travel applications. Currently there are many cameras monitoring crowds at airports for detecting wanted terrorists.
Corrections -This refers to the treatment of offenders criminals through a system of penal incarceration, rehabilitation, probation, and parole, or the administrative system by which these are effectuated. Is this cases a biometric system can avoid the possibility of accidentally releasing the wrong prisoner, or to ensure that people leaving the facilities are really visitors and not inmates. An AFIS is the primary system used for locating duplicates enrolls in benefits systems, electronic voting for local or national elections, driver's license emission, etc.
The typical application are: National Identification Cards - the idea is to include digital biometric information in the national identification card. This is the most ambitious biometric program, since the identification must be performed in a large-scale database, containing hundred of millions samples, corresponding to the whole population of one country. This kind of cards can be used for multiple purposes such as controlling the collection of benefits, avoiding duplicates of voter registration and drivers license emission.
All this applications are primarily based on finger-scan and AFIS technology, however it is possible that facial-scan and iris-scan technology could be used in the future. Voter ID and Elections - while the biometric national ID card is still in project, in many countries are already used the biometry for the control of voting and voter registration for the national or regional elections.
During the registration of voter, the biometric data is captured and stored in the card and in the database for the later use during the voting. The purpose is to prevent the duplicate registration and voting. Driver's licenses - In many countries the driver license is also used as identification document, therefore it is important to prevent the duplicate emission of the driver license under different name.
With the use of biometric this problem can be eliminated. Benefits Distribution social service - the use of biometry in benefits distribution prevents fraud and abuse of the government benefits programs. Ensuring that the legitimate recipients have a quick and convenient access to the benefits such as unemployment, health care and social security benefits. Employee authentication - The government use of biometric for PC, network, and data access is also important for security of building and protection of information.
Below are more detailed this kind of applications also used in commercial sector. Some applications in this sector are: Account access - The use of biometric for the access to the account in the bank allows to keep definitive and auditable records of account access by employees and customers. Using biometry the the customers can access accounts and employees can log into their workstations. Currently, there are many pilot programs using biometric in home banking.
In this type of application, when the costumer calls to make a transaction, a biometric system will authenticate the customer's identity based on his or her voice with no need of any additional device.
The main aim of biometrics is to prevent fraud, protect the patient information and control the sell of pharmaceutical products. Patient identification - In case of emergency, when a patient does not have identification document and is unable no communicate, biometric identification may be a good alternative to identify.
Typical application are: o Air travel - In many airport are already used a biometric system in order to reduce the inspection processing time for authorized travelers. The use of biometrics prevent the emission of multiple passports for the same person and also facilitates the identification at the airports and border controls. It combines computer vision, pattern recognition, statistical inference and optics. Of all the biometric devices and scanners available today, it is generally conceded that iris recognition is the most accurate.
The automated method of iris recognition is relatively young, existing in patent since only Figure 7. That encrypted template cannot be re-engineered or reproduced in any sort of visual image. Iris recognition therefore affords the highest level defence against identity theft, the most rapidly growing crime. The imaging process involves no lasers or bright lights and authentication is essentially non- contact. Today's commercial iris cameras use infrared light to illuminate the iris without causing harm or discomfort to the subject.
The iris is the coloured ring around the pupil of every human being and like a snowflake, no two are alike. The iris is a muscle that regulates the size of the pupil, controlling the amount of light that enters the eye.
This scan is digitally processed to create a biometric template which is stored and used for matching. It is also used in video surveillance, human computer interface and image database management. A face camera is a webcam with 2 Mpx or above which can take a clear crisp photograph of the face.
Also, face detection is useful for selecting regions of interest in photo slideshows that use a pan-and-scale Ken Burns effect. That is, the content of a given part of an image is transformed into features, after which a classifier trained on example faces decides whether that particular region of the image is a face, or not.
A face model can contain the appearance, shape, and motion of faces. There are several shapes of faces. Some common ones are oval, rectangle, round, square, heart, and triangle.
Motions include, but not limited to, blinking, raised eyebrows, flared nostrils, wrinkled forehead, and opened mouth. Biometric technology is now being used in almost every area. Not only that, but various types of biometric systems are being used to achieve various functionalities. There are many mature biometric systems available now.
Proper design and implementation ofthe biometric system can indeed increase the overall security. There are numerous conditionsthat must be taken in account when designing a secure biometric system. First, it is necessary torealize that biometrics is not secrets. This implies that care should be taken and it is not secureto generate any cryptographic keys from them.
Second, it is necessary to trust the input deviceand make the communication link secure. Third, the input device needs to be verified. The challenge has been to turn these into electronic processes that are inexpensive and easy to use. Banks and others who have tested biometric-based security on their clientele, however, say consumers overwhelmingly have a pragmatic response to the technology.
Anything that saves the information-overloaded citizen from having to remember another password or personal identification number comes as a welcome respite. Biometrics can address most of the security needs, but at what cost? Surprisingly, the benefits quickly outweigh the costs. Like so many technological developments, innovative people have found new ways to implement biometric systems, so prices have come down dramatically in the last year or two.
As prices have come down, the interest level and the knowledge about how to effectively utilize these systems have increased. So the investment is decreasing and the recognizable benefits are increasing.
Biometrics, when properly implemented, not only increase security but also often are easier to use and less costly to administer than the less secure alternatives.
Donis, L. Reyzin and A. Tuyls, B. Skoric and T. Kevenaar, Eds. Missing an occasional class is not the end of the world. Professors understand that you may become sick or have other legitimate reasons to not be in class. If you come to class on a regular basis and participate, your instructor will know that missing class is not the norm for you. Let your professor know that you will not be in class. Get class notes from a fellow classmate. Some college faculties believe that students should be allowed to decide whether to attend class.
Others believe that attendance should be mandatory. Regardless of your opinion, expectations regarding attendance should be clearly explained for each class. Attendance objectives should also be attainable. Students are often more willing to comply with policies when they understand why the policies exist. Communicating attendance expectations conveys a level of adult-to-adult respect between students and faculty. Remember, there may be consequences for missing class. These consequences should be conveyed along with attendance policies.
Realize that going to class is not a decision that needs to be made. The first, which is the older and is used in biological studies, including forestry, is the collection, synthesis, analysis and management of quantitative data on biological communities such as forests. Biometrics in reference to biological sciences has been studied and applied for several generations and is somewhat simply viewed as "biological statistics".
Authentication is the act of establishing or confirming something or someone as authentic, that is, that claims made by or about the thing are true European explorer Joao de Barros recorded the first known example of fingerprinting, which is a form of biometrics, in China during the 14th century.
Chinese merchants used ink to take children's fingerprints for identification purposes. In , Alphonse Bertillon studied body mechanics and measurements to help in identifying criminals.
The police used his method, the Bertillonage method, until it falsely identified some subjects. The Bertillonage method was quickly abandoned in favor of fingerprinting, brought back into use by Richard Edward Henry of Scotland Yard.
He made important discoveries in the field of biometrics through studying statistical history and correlation, which he applied to animal evolution.
His historical work included the method of moments, the Pearson system of curves, correlation and the chi-squared test. In the s and '70s, signature biometric authentication procedures were developed, but the biometric field remained fixed until the military and security agencies researched and developed biometric technology beyond fingerprinting.
Biometrics authentication is a growing and controversial field in which civil liberties groups express concern over privacy and identity issues. Today, biometric laws and regulations are in process and biometric industry standards are being tested.
Face recognition biometrics has not reached the prevalent level of fingerprinting, but with constant technological pushes and with the threat of terrorism, researchers and biometric developers will stimulate this security technology for the twenty-first century. Some examples in this case are signature, keystroke dynamics and of voice.
Sometimes voice is also considered to be a physiological biometric as it varies from person to person. A biometric system can provide two functions. One of which is verification and the other is Authentication. So, the techniques used for biometric authentication has to be stringent enough that they can employ both these functionalities simultaneously. Currently, cognitive biometrics systems are being developed to use brain response to odor stimuli, facial perception and mental performance for search at ports and high security areas.
Other biometric strategies are being developed such as those based on gait way of walking , retina, Hand veins, ear canal, facial thermogram, DNA, odor and scent and palm prints.
In the near future, these biometric techniques can be the solution for the current threats in world of information security. Of late after a thorough research it can be concluded that approaches made for simultaneous authentication and verification is most promising for iris, finger print and palm vain policies. So, application of Artificial System can be a solution for these cases. We have given emphasis on the Iris recognition. According to us, after detection of an iris pattern, the distance between pupil and the iris boundary can be computed.
This metric can be used for the recognition purposes because this feature remains unique for each and every individual. Again, an artificial system can be designed which will update the stored metric as the proposed feature may vary for a particular person after certain time period.
After doing the manual analysis of the above discussed method, we have got a satisfactory result. Due to the dynamic modification of the proposed metric, the rejection ration for a same person reduces by a lot. The work is being carried out to make the system viable. Biometrics is automated method of recognizing a person based on a physiological or behavioral characteristic.
Biometrics though in its nascent form has a number of tractable aspects like security, data integrity, fault tolerance and system recovery. It is considered a reliable solution for protecting the identity and the rights of individuals as it recognizes unique and immutable features. The comparator matches the obtained biometric with the ones stored in the database bank using a 1:N matching algorithm for identification.
A basic identity e. The validity of a biometric system cannot be measured accurately, and can only be enumerated on the occurrence of errors like the chance of accepting an intruder i. To capture the fingerprints, current techniques employ optical sensors that use a CCD or CMOS image sensor; solid state sensors that work on the transducer technology using capacitive, thermal, electric field or piezoelectric sensors; or ultrasound sensors that work on echography in which the sensor sends acoustic signals through the transmitter toward the finger and captures the echo signals with the receiver.
Fingerprint scanning is very stable and reliable. Recently a small number of banks have begun using fingerprint readers for authorization at ATMs. Face Recognition technique records face images through a digital video camera and analyses facial characteristics like the distance between eyes, nose, mouth, and jaw edges.
These measurements are broken into facial planes and retained in a database, further used for comparison. The distinctiveness of the face is captured without being oversensitive to noise such as lighting variations. Face recognition is then a matter of matching constellations. This non-intrusive technique is light-independent and not vulnerable to disguises. Even plastic surgery, cannot hinder the technique. This technique delivers enhanced accuracy, speed and reliability with minimal storage requirements.
To prevent a fake face or mold from faking out the system, many systems now require the user to smile, blink, or otherwise move in a way that is human before verifying. This technique is gaining support as a potential tool for averting terrorism, law enforcement areas and also in networks and automated bank tellers. Voice Recognition combines physiological and behavioral factors to produce speech patterns that can be captured by speech processing technology. Inherent properties of the speaker like fundamental frequency, nasal tone, cadence, inflection, etc.
The matching is done by the system on the basis of the fundamental voice patterns irrespective of the language and the text used. The vocal-tract is represented in a parametric form as the transfer function H z. Ideally, the transfer function should contain poles as well as zeros.
However, if only the voiced regions of speech are used then an all-pole model for H z is sufficient. Furthermore, linear prediction analysis can be used to efficiently estimate the parameters of an all-pole model.
Finally, it can also be noted that the all-pole model is the minimum-phase part of the true model and has an identical magnitude spectra, which contains the bulk of the speaker-dependent information. This technique is inexpensive but is sensitive to background noise and it can be duplicated.
Also, it is not always reliable as voice is subject to change during bouts of illness, hoarseness, or other common throat problems. Applications of this technique include voice-controlled computer system, telephone banking, m-commerce and audio and video indexing.
Iris Recognition analyzes features like rings, furrows, and freckles existing in the colored tissue surrounding the pupil. The scans use a regular video camera and works through glasses and contact lenses. The image of the iris can be directly taken by making the user position his eye within the field of a single narrow-angle camera. This is done by observing a visual feedback via a mirror.
The isolated iris pattern obtained is then demodulated to extract its phase information. The system captures images with the iris diameter typically between pixels from a distance of cm using mm lens.
The system images the iris with approximately pixels across the diameter from 20cm using an 80mm lens. Also it is used a Berkshire County jail for prisoner identification and Frankfurt airport for passenger registration. Hand geometry, as the name suggests, involves the measurement and analysis of the human hand. Features like length and width of the fingers, aspect ratio of the palm or fingers, width of the palm, thickness of the palm, etc. The user places the palm on a metal surface, which has guidance pegs on it to properly align the palm, so that the device can read the hand attributes.
To enroll a person in a database, two snapshots of the hand are taken and the average of resulting feature vectors is computed and stored. Four different distance matrices Absolute, weighted Absolute, Euclidean and weighted Euclidean. Hand Vascular Pattern Identification uses a non-harmful near infrared light to produce an image of one's vein pattern in their face, wrist, or hand, as veins are relatively stable through one's life.
It is a non-invasive, computerized comparison of shape and size of subcutaneous blood vessel structures in the back of a hand. The vein "tree" pattern, picked up by a video camera, is sufficiently idiosyncratic to function as a personal code that is extremely difficult to duplicate or discover.
The sensor requires no physical contact, providing excellent convenience and no performance degradation even with scars or hand contamination. Verification speed of the system is fast 0. Though minimally used at the moment, vascular pattern scanners can be found in testing at major military installations and is being considered by some established companies in the security industry and multi-outlet retailers.
Retina Recognition technology uses infrared scanning and compares images of the blood vessels in the back of the eye, the choroidal vasculature. Retina scan is used in high- end security applications like military installations and power plants. The way a person signs his name is known to be a characteristic of that individual. Approach to signature verification is based on features like number of interior contours and number of vertical slope components.
Signatures are behavioral biometric that can change with time, influenced by physical and emotional conditions of the signatories. Furthermore, professional forgers can reproduce signatures to fool an unskilled eye and hence is not the preferred choice.
DNA Recognition employs Deoxyribo Nucleic Acid, which is the one-dimensional ultimate unique code for ones individuality, except for the fact that identical twins have identical DNA patterns. However, it is currently used mostly used in the context of forensic applications. The basis of DNA identification is the comparison of alleles of DNA sequences found at loci in nuclear genetic material.
A set of loci is examined to determine which alleles have been identified. However, issues like contamination, sensitivity, and automatic real-time recognition limit the utility of this biometric.
The probability of 2 people sharing the same biometric data is virtually nil. Cannot be shared: Because a biometric property is an intrinsic property of an individual, it is extremely difficult to duplicate or share you cannot give a copy of your face or your hand to someone! Cannot be copied: Biometric characteristics are nearly impossible to forge or spoof, especially with new technologies ensuring that the biometric being identified is from a live person.
Cannot be lost: A biometric property of an individual can be lost only in case of serious accident. A database management system DBMS is a software package with computer programs that control the creation, maintenance, and the use of a database A data captured by an information system is stored in files and databases. A file is a collection of similar records while a database is a collection of interrelated files. Database design is the process of translating logical data model into physical database schemas.
A database schema of a database system is its structure described in a formal language supported by the database management system DBMS and refers to the organization of data to create a blueprint of how a database will be constructed divided into database tables.
A database system offers scalability, data sharing among user groups, balancing of conflicting user requirements, enforcement of standards, controlled redundancy, effective security, flexibility and data dependency.
DBase, FoxPro etc. These database objects include schemas, tables, views, sequences, catalogues, indexes, and aliases. A popular data manipulation language is that of Structured Query Language SQL , which is used to retrieve and manipulate data in a relational database.
According to w3schools. It is an ANSI standard computer language, allows you to access a database, can execute queries against a database, can retrieve data from a database and it is easy to learn. Early in its history, MySQL occasionally faced opposition due to its lack of support for some core SQL constructs such as sub selects and foreign keys. Ultimately, however, MySQL found a broad, enthusiastic user base for its liberal licensing terms, perky performance, and ease of use.
Its acceptance was aided in part by the wide variety of other technologies such as PHP, Java, Perl, Python, and the like that have encouraged its use through stable, well-documented modules and extensions. MySQL has not failed to reward the loyalty of these users with the addition of both sub selects and foreign keys as of the 4. VisualC C pronounced "C sharp" is a programming language that is designed for building a variety of applications that run on the.
NET Framework. C is simple, powerful, type-safe, and object- oriented. The many innovations in C enable rapid application development while retaining the expressiveness and elegance of C-style languages. Visual C is an implementation of the C language by Microsoft. Visual Studio supports Visual C with a full-featured code editor, compiler, project templates, designers, code wizards, a powerful and easy-to-use debugger, and other tools.
C is introduced as Visual C in the Visual Studio. NET suite. The new matching schemes include direction only feature, density only feature, two channels with addition-type fusion, two channels with multiplication-type fusion and two templates per class. At the end, simulations are performed in order to test the performance of the improvements implemented in the automatic fingerprint identification system. Handbook provides authoritative and comprehensive coverage of all major topics, concepts, and methods for fingerprint security systems.
This unique reference work is an absolutely essential resource for all biometric security professionals, researchers, and systems administrators. This book is the most comprehensive study of this field. It contains a collection of 78 carefully selected articles contributed by experts of pattern recognition.
It reports on current research with respect to both methodology and applications. In particular, it includes the following sections: Biometrics, Features, learning and classifiers, Image processing and computer vision, Knowledge acquisition based on reasoning methods Medical applications, Miscellaneous applications, This book is a great reference tool for scientists who deal with the problems of designing computer pattern recognition systems.
Its target readers can be as well researchers as students of computer science, artificial intelligence or robotics. The present work concerned with study fingerprint recognition system by using image processing techniques. This work is an attempt to recognize fingerprint among many fingerprints that store in small data base by using image processing techniques. These fingerprints must be edge detection by using 'Laplacian filter' but this filter considered with all details that do not needed in our work so we need to image smoothing and using mean filter.
After this operation finger print image must be converted to binary image because thinning algorithm depended on 0,1. Then determined End point and all possible Directions vertical line, horizontal line, diagonal line 95, , multi junction then determine the center point and determined core point automatically by using mouse down then find the distance between center point and core point and store the result in file for all fingerprint images.
The revised full papers presented were carefully reviewed and selected from submissions. Biometric criteria covered by the papers are assigned to face, fingerprint, iris, speech and signature, biometric fusion and performance evaluation, gait, keystrokes, and others.
The program committee selected carefully revised full papers and short papers for presentation in three volumes from submissions. The first volume includes all the contributions related to learning algorithms and architectures in neural networks, neurodynamics, statistical neural network models and support vector machines, and other topics in neural network models; cognitive science, neuroscience informatics, bioinformatics, and bio-medical engineering, and neural network applications as communications and computer networks, expert system and informatics, and financial engineering.
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