MACHINE LEARNING SunawaR KhaN Islamia University of Bahawalpur Bahawalnagar Campus Contents What is Biometrics? Types of Biometric Recognition Applications of Biometric Systems Types of Authentication Constraints on Biometrics Biometric Research at Clemson سنور خان Biometric Recognition Introduction • The term biometric comes form the Greek words bios(life) and metrikos(measure). • It is well known that humans intuitively use some body characteristics such as face, gait or voice to recognize each other. • It is the study of physical or behavioral characteristics used for identification of a person. • For many applications of biometric, the system uses the password as well as biometrics for authentication. سنور خان Biometric Recognition What is Biometrics Automated method for recognizing individuals based on measurable biological and behavioral characteristics سنور خان Biometric Recognition Two meanings of biometrics • Biometrics as a part of Computer Science • measurement of physical of behavioral properties of human beings • aim of the measurement defined: automatic identity recognition • Biometrics = use of physical or behavioral properties of human beings for automatic identity recognition سنور خان Biometric Recognition Problem with Current Security Systems • Based on Passwords, or ID/Swipe cards • Can be Lost. • Can be forgotten. • Worse! Can be stolen and used by a thief/intruder to access your data, bank accounts, car etc • With increasing use of IT technology and need to protect data, we have multiple accounts/passwords. • We can only remember so many passwords, so we end up using things we know to create them (birthdays, wife/girlfriends name, dog, cat…) • Its is easy to crack passwords, because most of our passwords are weak! • If we create strong passwords (that should be meaningless to us) we will forget them! And there is no way to remember multiple such passwords سنور خان Biometric Recognition Some statistics on User/Passwords • Case Study: Telesis Community Credit Union(CA), a California based financial services provider that manages $1.2 billion in assets. • The VP of IT, lead a team to run a network password cracker as part of an enterprise security audit last year to see if employees were following Telesis’ password policies. • Result: They were far from doing so…. • In fact within 30 seconds the team was able to identify 80% of people’s passwords! • The team asked employees to change their passwords and comply with password policies. • A few days later, the IT team run their password cracking exercise again…. • This time they still were able to crack 70% of the passwords! سنور خان Biometric Recognition Example • The identification of a person is becoming highly important as the ID cards, punch, secret password and PIN are used for personal identification. • The ID can be stolen; passwords can be forgotten or cracked. • The biometric identification overcomes all the above. • Additional security barriers can be provided using any one of the biometrics features. • The features like fingerprints, face, hand geometry, voice, and iris. • These biometrics features can be used for authentication purpose in computer based security systems. سنور خان Biometric Recognition Some Examples of Different Biometris • Here are few • Face • Fingerprint • Voice • Palmprint • Hand Geometry • Iris • Retina Scan • Voice • DNA • Signatures • Gait • Keystroke سنور خان Biometric Recognition Applications + Terminology • Identification: – Match a person’s biometrics against a database to figure out his identity by finding the closest match. – Commonly referred to as 1:N matching – ‘Criminal Watch-list’ application scenario • Verification: – The person claims to be ‘John’, system must match and compare his/hers biometrics with John’s stored Biometrics. – If they match, then user is ‘verified’ or authenticated that he is indeed ‘John’ – Access control application scenarios. – Typically referred as 1:1 matching. سنور خان Biometric Recognition Types • Biometrics measures biological characteristics for identification or verification purposes of an individual. • Since IDs and passports can be forged, more sophisticated methods needed to be put into place to help protect companies and individuals. • There are two types of biometric methods. • One is called Physiological biometrics used for identification or verification purposes. Identification refers to determining who a person is. This method is commonly used in criminal investigations. • Behavioral biometrics is the other type. It is used for verification purposes. Verification is determining if a person is who they say they are. This method looks at patterns of how certain activities are performed by an individual. سنور خان Biometric Recognition Figure سنور خان Biometric Recognition Finger Print Recognition • Minutiae • Pattern Matching • Problems: sometimes unusable سنور خان Biometric Recognition Vascular Pattern Matching • LED infrared light • Fingers and back of hand • Not completely viable سنور خان Biometric Recognition Iris Recognition • Uses infrared light • Converts Images to vectors • Needs further development سنور خان Biometric Recognition Iris Recognition • Hand geometry systems produce estimates of certain measurements of the hand such as the length and the width of fingers. • Various methods are used to measure the hand. • These methods are most commonly based either on mechanical or optical principle. • The latter ones are much more common today. • The hand geometry is used for identification and recognition of a person. سنور خان Biometric Recognition Facial Recognition • Location and position of facial features • Dependent on background and lighting conditions سنور خان Biometric Recognition Facial Recognition • Facial recognition is the most natural means of biometric identification. The approaches to face recognition are based on shape of facial attributes, such as eyes, eyebrows, nose, lips, chin and the relationships of these attributes. • As this technique involves many facial elements; these systems have difficulty in matching face images سنور خان Biometric Recognition D.N.A. • DNA(Deoxyribonucleic Acid) sampling is rather intrusive at present and requires a form of tissue, blood or other bodily sample. • This method of capture still has to be refined. • So far the DNA analysis has not been sufficiently automatic to rank the DNA analysis as a biometric technology. • The analysis of human DNA is now possible within 10 minutes. • As soon as the technology advances so that DNA can be matched automatically in real time, it may become more significant. • At present DNA is very entrenched in crime detection and so will remain in the law enforcement area for the time being سنور خان Biometric Recognition Voice Verification • Factors: pitch, intensity, quality and duration • Text dependent • Text independent • Problems: include background noise سنور خان Biometric Recognition Voice Recognition • The features of an individual's voice are based on physical characteristics such as vocal tracts, mouth, nasal cavities and lips that are used in creating a sound. • These characteristics of human speech are invariant for an individual, but the behavioral part changes over time due to age, medical conditions and emotional state. • Voice recognition techniques are generally categorized according to two approaches: 1) Automatic Speaker Verification (ASV) and 2) Automatic Speaker Identification (ASI). • Speaker verification uses voice as the authenticating attribute in a two-factor scenario. سنور خان Biometric Recognition Hand Geometry • Scan both sides of hand • Primarily used for verification • Not as accurate as other methods سنور خان Biometric Recognition Dynamic Signature • Factors: velocity, acceleration and speed • Mainly used for verification • Problems: forgers could reproduce سنور خان Biometric Recognition Signature Verification • The way a person signs his or her name is known to be characteristic of that individual. • Signature is a simple, concrete expression of the unique variations in human hand geometry. • Collecting samples for this biometric includes subject cooperation and requires the writing instrument. • Signatures are a behavioral biometric that change over a period of time and are influenced by physical and emotional conditions of a subject. • In addition to the general shape of the signed name, a signature recognition system can also measure pressure and velocity of the point of the stylus across the sensor pad. سنور خان Biometric Recognition Retina Recognition • One of the most secure means of biometrics • Unique to each person • Unique to each eye • Problems: require effort on the part of subjects سنور خان Biometric Recognition Other Types • Keystroke • Gait • DNA • Odor سنور خان Biometric Recognition Commercial Applications • Computer login • Electronic Payment • ATMs • Record Protection سنور خان Biometric Recognition Government Applications • Passport control • Border control • Access Control سنور خان Biometric Recognition Forensic Applications • Missing Persons • Corpse identification • Criminal investigations سنور خان Biometric Recognition Type of Authentication • Authentication • 1:1 • Verification • 1:N سنور خان Biometric Recognition Constraints on Biometrics • Typical “Constrained” Image • Constraints: • • • • • • Lighting Distance Pose Expression Time Lapse Occlusion سنور خان Biometric Recognition Constraints on Biometrics • “Unconstrained” Image سنور خان Biometric Recognition Keystroke • Keyboard- is the part that helps us to communicate with computer. • People use keyboard in different ways. Some people type fast, some slow. The speed of the typing also depends on the mood of a person and a time of a day. • Biometric keystroke recognition – is a technology of recognizing people from the way they are typing. • It is rather important to understand that this technology does not deal with “what” is written but “how” it is written. سنور خان Biometric Recognition Biometrics Research at Clemson • Biometric and Pattern Recognition Lab • Goals: 1. Usable Biometrics 2. Unconstrained Biometrics سنور خان Biometric Recognition Biometrics Research at Clemson • Aging Research سنور خان Biometric Recognition Biometrics Research at Clemson • Demographics • Older vs. Younger • Males vs. Females • Geographic origin of algorithms سنور خان Biometric Recognition Biometrics Research at Clemson • Periocular Region Recognition • Texture, color, eye shape • Overcome facial occlusion سنور خان Biometric Recognition Biometrics Research at Clemson • Ear Recognition • Not affected by aging or expression • Covert collection of images • Little research performed سنور خان Biometric Recognition
