102 of biometric enrolment

TalkingBiometrics@ITREALMS:

We introduced biometric enrolment in the previously edition, we shall now examine specific scenarios.

The environment where a biometric enrolment activity takes place is known as an enrolment center, and it can be as elaborate as a dedicated office, or as simple as a mobile van or a temporary location specifically designated for this purpose.

Temporary enrolment centres can be set up in schools, churches, mosques, markets, sports arenas, airports, train stations, shopping malls, or other convenient locations suitable for such makeshift arrangement. Factors that determine the location of a temporary biometric enrolment centre include safety of equipment and personnel, access to power supply, space for enrollee queue, etc. The type of biometric system adopted also determines whether it is suitable for outdoor use or strictly indoor operations.

Fingerprint technology is a widely adopted biometric system used in a number of enrolment cases. For effective fingerprint enrollment, clean scanners are essential to minimize failures and guarantee hygiene. Although there may be difficulties with easy collection of fingerprint samples from infants, it is generally accepted for most identity management schemes for verification because of the distinctiveness of human finger patterns from person to person. For this reason, fingerprints can be used in both single biometric verification systems and multi-modal systems where they are simultaneously used together with other biometrics such as facial or iris patterns. Multi-modal biometric implementations guarantee

…to be continued.

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About The Columnist

Kenneth Okereafor is an accomplished ICT professional and Cybersecurity expert with over 20 years computing experience in Enterprise ICT innovation management in both private and public sectors. He holds dual PhD degrees in Computer Science (Cybersecurity & Biometrics) and Management (ICT Administration and Governance) with a first class Electronics & Telecommunications Engineering background. He is a United Nations trained Network Security Specialist and is proficient in Network Optimization, Data Protection, Biometric Systems and Digital Forensics. In addition to many published works and conference papers, Kenneth has participated at many international technology events, and has contributed to several national ICT development programmes including the design and development of the National eHealth Strategic Framework 2015 - 2020. He has strong research interests in Digital Innovations, Cloud Security, Cybersecurity Education, Biometric Liveness Detection and Green Computing; and may be reached at nitelken@yahoo.com

101 of biometric enrolment

TalkingBiometrics@ITREALMS:

 

In the digital identity domain, Biometric Enrolment is the process of using a biometric equipment to collect an individual’s biometric information for the purpose of using the captured information in future to recognize, verify or identify that individual. The person whose biometric information is so captured is known as the enrollee.

Biometric enrolment is a one-off operation and is not the same thing as biometric verification, recognition, or identification which can be undertaken as often as necessary. The initial enrolment process captures the individual’s biometric information, while future verification uses previously-stored information to verify or confirm his/her identity.

In practice, the biometric enrolment process involves the use of a specific biometric system to capture the biometric image in one of various scenarios illustrated in the three figures below.

Figure 1: Fingerprint captured using fingerprint scanners.

 Figure 2: Facial image captured using facial recognition system.

Figure 3: Iris pattern captured using appropriate eye biometrics equipment.

Each biometric equipment contains a scanner which obtains the actual biometric image from the enrollee. The processed image is changed into electronic form and stored on the equipment. Nearly all biometric equipment have the capacity to send the captured information to a remote database for security and centralized access.

…to be continued.

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About The Columnist

Kenneth Okereafor is an accomplished ICT professional and Cybersecurity expert with over 20 years computing experience in Enterprise ICT innovation management in both private and public sectors. He holds dual PhD degrees in Computer Science (Cybersecurity & Biometrics) and Management (ICT Administration and Governance) with a first class Electronics & Telecommunications Engineering background. He is a United Nations trained Network Security Specialist and is proficient in Network Optimization, Data Protection, Biometric Systems and Digital Forensics. In addition to many published works and conference papers, Kenneth has participated at many international technology events, and has contributed to several national ICT development programmes including the design and development of the National eHealth Strategic Framework 2015 - 2020. He has strong research interests in Digital Innovations, Cloud Security, Cybersecurity Education, Biometric Liveness Detection and Green Computing; and may be reached at nitelken@yahoo.com

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7 Pillars of biometric (3)

TalkingBiometrics@ITREALMS:

 

In this edition we discuss the last two pillars of biometrics: permanence and acceptability.  

6: Permanence

It is common to experience that some biometric features naturally undergo more changes than others, thereby resulting in a gradual reduction in their performance as time passes. Example, human voice is said to be affected by age, weather, and medical conditions. Fingerprints also get affected by injury, weather, cosmetics and corrosive creams. On the other hand, retina patterns remain significantly stable throughout an individual’s lifetime irrespective of eye defects. Retina is the reddish layer at the back of the eyeball which carries light impulses to the brain.

Permanence is the extent to which the trait resists the effects of aging and environmental conditions, and is able to withstand changes over a period of time. In making a choice of biometric for adoption, it is expected that the trait quality should remain minimally unchanged throughout the individual’s life, and that the modality should remain considerably stable over time.

7: Acceptability

Biometric acceptability is how readily users are able to accept to use it. The willingness to accept a biometric trait or to comply with its processes define the level of users’ approval and acceptability. There are a lot of reasons why people may choose a particular biometric in place of another, a few of them are listed below:

(i)            Intrusiveness: If it is difficult to use or if it requires special postures and repeated gestures, users will avoid it. Example, some facial recognition systems require the user’s face to be well illuminated, be tilted at an angle, maintain a certain distance from the camera, or put up a smiley face. Such requirements are regarded by some users as inconveniencing, compelling and therefore too intrusive.

(ii)          Hygiene: If the biometric system causes real or potential harm, users will be discouraged to use it. Example, during the ebola outbreak in some parts of Africa in 2014, fingerprint scanners were avoided due to hygiene concerns, leading to the adoption of facial recognition and other forms of contactless biometric systems as ready alternatives.

(iii)         Religious and cultural beliefs: Some cultural beliefs and religious doctrines forbid people from sharing public facilities such as biometric centres with the opposite gender other than their spouses. In such areas, biometric enrolment suffers great apathy.

(iv)         Data privacy: Biometric data is usually classified as private, therefore some users especially bank customers shy away from supplying biometric samples, especially where they suspect that adequate security provisions have not been made to protect their biometric information.

(v)          Limited versatility: A biometric trait or system is said to be versatile if it can be used successfully in a wide range of commercial and industrial applications without performance problems. The more versatile a biometric system is, the more it becomes generally accepted. Versatile biometrics are mostly used in voice, finger and eye-based recognition systems.

…to be continued.

ITREALMS ... everything news digitally!

About The Columnist

Kenneth Okereafor is an accomplished ICT professional and Cybersecurity expert with over 20 years computing experience in Enterprise ICT innovation management in both private and public sectors. He holds dual PhD degrees in Computer Science (Cybersecurity & Biometrics) and Management (ICT Administration and Governance) with a first class Electronics & Telecommunications Engineering background. He is a United Nations trained Network Security Specialist and is proficient in Network Optimization, Data Protection, Biometric Systems and Digital Forensics. In addition to many published works and conference papers, Kenneth has participated at many international technology events, and has contributed to several national ICT development programmes including the design and development of the National eHealth Strategic Framework 2015 - 2020. He has strong research interests in Digital Innovations, Cloud Security, Cybersecurity Education, Biometric Liveness Detection and Green Computing; and may be reached at nitelken@yahoo.com

Seven Pillars of Biometrics (Part 2)

TalkingBiometrics@ITREALMS:

In this edition, we would continue discussion on the characteristics that determine the suitability of a human trait as a biometric attribute, otherwise called the seven pillars of biometrics.

4: Circumvention or Security

A measure of how easy it can be to fool a given attribute is an indication of its suitability (or otherwise) for biometric purposes. Circumvention is a quality that evaluates the ease with which a biometric trait can be fooled or bypassed by an attacker and to what extent it can withstand being spoofed or defeated. The measure or degree of difficulty required to bypass a biometric trait is an indication of its security and usability as a biometric authentication technique, and also a pointer to how vulnerable it might become to spoof attacks and identity fraud.

It is common occurrence for two separate individuals to have the similar height or exactly same weight, but it is rare to obtain a perfectly similar facial pattern or fingerprint from two persons. This is why height and weight cannot be used as classical biometric attributes, but facial pattern and fingerprints can be used because it is difficult to obtain such similar values from different persons, hence they are more secure. It is also more difficult (but not totally impossible) to fabricate fake eyeballs or retina patterns than to obtain fake signatures. 

In this sense we say that even though both offer relatively high levels of security as biometric attributes, retina patterns are more difficult to circumvent or forge than signatures, thereby making retina patterns a more secure set of biometric attributes than signatures, and a more preferred option for use at maximum security facilities. Vein patterns have also been known to exhibit a more secure biometric characteristics than voice prints.

5: Performance

Biometric performance is a measure of the speed and accuracy of recognizing the trait while in normal use even in the midst of environment effects. It is an indication of how well the biometric trait is able to compensate for inherent losses during the processing of the samples. In general biometric performance is closely tied to its efficiency to successfully complete the identification or authentication processes in a timely manner while minimizing errors. 

As an illustration, it is faster and more probable to process 3D facial patterns from babies and infants than to recognize their fingerprints. This is because fingerprint formation naturally takes time to become fully-usable as a biometric trait, resulting in the poor quality of fingerprint processes often experienced with toddlerbiometrics. In this sense, we say that facialprints have better infant-related performance than fingerprints.

… To be continued next week.

ITREALMS ... everything news digitally!

About The Columnist

Kenneth Okereafor is an accomplished ICT professional and Cybersecurity expert with over 20 years computing experience in Enterprise ICT innovation management in both private and public sectors. He holds dual PhD degrees in Computer Science (Cybersecurity & Biometrics) and Management (ICT Administration and Governance) with a first class Electronics & Telecommunications Engineering background. He is a United Nations trained Network Security Specialist and is proficient in Network Optimization, Data Protection, Biometric Systems and Digital Forensics. In addition to many published works and conference papers, Kenneth has participated at many international technology events, and has contributed to several national ICT development programmes including the design and development of the National eHealth Strategic Framework 2015 - 2020. He has strong research interests in Digital Innovations, Cloud Security, Cybersecurity Education, Biometric Liveness Detection and Green Computing; and may be reached at nitelken@yahoo.com

Pillars of biometrics

TalkingBiometrics@ITREALMS:

Preamble:

In this edition, we will discuss seven characteristics that qualify any human attribute to be considered fit as a biometric item. These seven characteristics are together called the pillars of biometrics

Seven Pillars of biometrics:

Most people wonder what makes a biological characteristic fit for biometric use. For a human measurable quantity (trait) to be considered suitable for use as a biometric item (eg fingerprint or voice print), it must possess seven basic qualities, collectively called the seven pillars of biometrics. We shall review each of these seven qualities and how they determine what qualifies as a biometric quantity, but let us first understand the difference between a biometric trait and a biometric modality.

Biometric triats vs. modality:

We defined biometrics earlier in the first edition as the human physiological or behavioural attributes that distinguish humans and used as a means of verifying or authenticating their identity into information systems. A modality is the human identifier from where these biometric characteristics are extracted, but a trait is that particular physiological or behavioural characteristic that is so extracted from modalities. In most cases the modality is a physiological part of the human body eg the eye or the hand, but can sometimes be a behavioural pattern eg human voice, walking style, signature, etc. This is illustrated in Table 1 below and shows examples of eight of the most commonly-used biometric traits and the corresponding modalities from where they are derived.

1: Universality

Biometric universality stipulates that for any characteristic to be suitable as a biometric item, all humans should possess the characteristic, and the modality should adequately differentiate between any two users. The trait must be universally existent in all individuals as a biological feature or a natural human characteristic, and each potential user must possess it. This explains why a horn is not suitable as a biometric attribute because humans do not grow horns. In other words, a horn is not a universal attribute in humans.

In contrast, traits such as the shape of the palm (palm geometry), blood pattern at the back of the eye (retina pattern), and human voice, all qualify as good biometric traits because of their widespread nature and the commonality of their characteristics from person to person, hence their universality. Every normal human has a hand, an eye, and can talk respectively. These modalities exist in all humans and their characteristic properties vary from one individual to another and hence are very usable as biometric traits and in biometric systems.

2: Uniqueness or Distinctiveness

The uniqueness of a biometric trait refers to its ability to distinguish between different individuals and ensure that each potential user possesses the modality from where it is derived. This quality is a strong factor in evaluating the suitability of a biometric entity, and it specifies that the characteristic of the modality should not appear similar in any two people. For this reason, fingerprints differ from person to person even in identical twins, iris patterns also differ between parents and their children, etc. It is the uniqueness of these traits from person to person that contribute to make them acceptable as biometric quantity.

3: Measurability or collectability

Biometric measurability pertains to the ease of measuring and presenting the trait quantitatively. It is the degree with which the biometric samples can be acquired, analyzed and converted into digital templates for the purpose of identification or verification. Measurability emphasizes that the trait samples should be easy to detect and acquire, eg the ease of scanning to obtain a fingerprint image from a thumb or to retrieve iris patterns from the eye using simple technical instruments and systems such as a thumb scanner or a voice recorder makes these quantities suitable for use as biometric traits.

In practical terms the ease of collecting and assembling trait samples for biometric use is a very important consideration in adopting a given method because certain biometrics by their nature and appearance pose serious difficulties during collection. Eg medical conditions such as throat inflammation can affect speech quality and make high quality voice prints difficult to obtain, injured finger can increase the difficulty of acquiring fingerprints. Similarly scars, marks, tattoos (SMT), or age-induced wrinkles can affect the measurability of facial pattern from the face modality.

Coming up next: We shall discuss the remaining pillars of biometrics including security, permanence, and others.

Talking Biometrics @ ITRealms with Dr. Ken is a weekly online column providing biometric education and associated electronic identity awareness.

About The Columnist

Kenneth Okereafor is an accomplished ICT professional and Cybersecurity expert with over 20 years computing experience in Enterprise ICT innovation management in both private and public sectors. He holds dual PhD degrees in Computer Science (Cybersecurity & Biometrics) and Management (ICT Administration and Governance) with a first class Electronics & Telecommunications Engineering background. He is a United Nations trained Network Security Specialist and is proficient in Network Optimization, Data Protection, Biometric Systems and Digital Forensics. In addition to many published works and conference papers, Kenneth has participated at many international technology events, and has contributed to several national ICT development programmes including the design and development of the National eHealth Strategic Framework 2015 - 2020. He has strong research interests in Digital Innovations, Cloud Security, Cybersecurity Education, Biometric Liveness Detection and Green Computing; and may be reached at nitelken@yahoo.com

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