What are biometrics?

“Biometric” come from the Greek words “bio” (life) and “metric” (to measure). Biometrics are technologies used for measuring and analyzing a person’s unique characteristics. There are two types of biometrics: behavioral and physical. Behavioral biometrics are generally used for verification while physical biometrics can be used for either identification or verification.

What are biometric systems used for?

Biometrics are used for identification and verification:

  • Identification is determining who a person is. It involves trying to find a match for a person’s biometric data in a database containing records of people and that characteristic. This method requires time and a large amount of processing power, especially if the database is very large.
  • Verification is determining if a person is who they say they are. It involves comparing a user’s biometric data to the previously recorded data for that person to ensure that this is the same person. This method requires less processing power and time, and is used for access control (to buildings or data).

What are the main types of biometric systems?

The main physical biometric technologies include:

  • fingerprint
  • iris
  • retina
  • hand
  • palm vein
  • face

There are also a number of behavioural biometric technologies such as voice recognition (analyzing a speaker’s vocal behavior), keystroke (measuring the time spacing of typed words), gait recognition (manner of walking), or signature (analyzing the way you sign).
Other biometric techniques, still in exploratory stages would include DNA biometrics, ear shape, fingernails or odor.

How biometric systems work

Biometric devices normally consist of 3 elements:

  • a scanner / reader that captures the user’s biometrics characteristics
  • a piece of software that converts this data into digital form and compares it with data previously recorded
  • a database, which stores the biometric data

The process comprises 4 main steps: sample capture, feature extraction, template comparison, and matching. At enrolment, a person’s biometrics is captured by the scanner. The software converts the biometric input into a template and identifies specific points of data as “match points”. The match points are processed using an algorithm into a value that can be compared with biometric data in the database.

What is the best biometric technology?

There is not one signle biometric technology that would be ideal for all applications. Each technology has its own benefits and weaknesses in terms of accuracy, cost, ease of use, intrusiveness, , ease of deployment.

Biometric systems offer many important benefits

Biometrics is concerned with identifying a person based on his / her physiological or behavioral characteristics. Examples of biometrics systems include fingerprint, hand, face, eye (iris or retina), and speech recognition.

Why are biometrics secure?

Unique: The various biometrics systems have been developed around unique characteristics of individuals. 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.

What are biometric systems used for?

Reliable user authentication is essential. The consequences of insecure authentication in a banking or corporate environment can be catastrophic, with loss of confidential information, money, and compromised data integrity. Many applications in everyday life also require user authentication, including physical access control to offices or buildings, e-commerce, healthcare, immigration and border control, etc.

Currently, the prevailing techniques of user authentication are linked to passwords, user IDs, identification cards and PINs (personal identification numbers). These techniques suffer from several limitations: Passwords and PINs can be guessed, stolen or illicitly acquired by covert observation.

In addition, there is no way to positively link the usage of the system or service to the actual user. A password can be shared, and there is no way for the system to know who the actual user is. A credit card transaction can only validate the credit card number and the PIN, not if the transaction is conducted by the rightful owner of the credit card.
This is where biometrics systems provide a more accurate and reliable user authentication method, as can be summarised in the table underneath:

Existing user authentication techniques include:

  • Something you know, e.g. password or PIN. The issue is that many password are easy to guess, and can also be easily forgotten.
  • Something you have, e.g. key or car. They can be lost, stolen or duplicated.
  • Something you know and have, e.g. card + PIN.
  • Something you are, e.g. fingerprint, hand, iris, retina, voice. You cannot lose them, are unique for each individual and are difficult to forge.

The issues with biometric systems

Recognition errors

There are two basic types of recognition errors: the false accept rate (FAR) and the false reject rate (FRR). A False Accept is when a nonmatching pair of biometric data is wrongly accepted as a match by the system. A False Reject is when a matching pair of biometric data is wrongly rejected by the system. The two errors are complementary: When you try to lower one of the errors by varying the threshold, the other error rate automatically increases. There is therefore a balance to be found, with a decision threshold that can be specified to either reduce the risk of FAR, or to reduce the risk of FRR.

In a biometric authentication system, the relative false accept and false reject rates can be set by choosing a particular operating point (i.e., a detection threshold). Very low (close to zero) error rates for both errors (FAR and FRR) at the same time are not possible. By setting a high threshold, the FAR error can be close to zero, and similarly by setting a significantly low threshold, the FRR rate can be close to zero. A meaningful operating point for the threshold is decided based on the application requirements, and the FAR versus FRR error rates at that operating point may be quite different. To provide high security, biometric systems operate at a low FAR instead of the commonly recommended equal error rate (EER) operating point where FAR = FRR.

Compromised biometric data

Paradoxically, the greatest strength of biometrics is at the same time its greatest liability. It is the fact that an individual’s biometric data does not change over time: the pattern in your iris, retina or palm vein remain the same throughout your life. Unfortunately, this means that should a set of biometric data be compromised, it is compromised forever. The user only has a limited number of biometric features (one face, two hands, ten fingers, two eyes). For authentication systems based on physical tokens such as keys and badges, a compromised token can be easily canceled and the user can be assigned a new token. Similarly, user IDs and passwords can be changed as often as required. But if the biometric data are compromised, the user may quickly run out of biometric features to be used for authentication.

Vulnerable points of a biometric system

The first stage involves scanning the user to acquire his/her unique biometric data. This process is called enrollment. During enrollment, an invariant template is stored in a database that represents the particular individual.

To authenticate the user against a given ID, this template is retrieved from the database and matched against the new template derived from a newly acquired input signal.

This is similar to a password: You first have to create a password for a new user, then when the user tries to access the system, he/she will be prompted to enter his/her password. If the password entered via the keyboard matches the password previously stored, access will be granted.


There are seven main areas where attacks may occur in a biometric system:

Presenting fake biometrics or a copy at the sensor, for instance a fake finger or a face mask. It is also possible to try and resubmitting previously stored digitized biometrics signals such as a copy of a fingerprint image or a voice recording.

Producing feature sets preselected by the intruder by overriding the feature extraction process.

Tampering with the biometric feature representation: The features extracted from the input signal are replaced with a fraudulent feature set.

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 – There is a real danger if the biometric feature set is transmitted over the Internet.

Corrupting the matcher: The matcher is attacked and corrupted so that it produces pre-selected match scores.

Tampering with stored templates, either locally or remotely.

Overriding the match result.

Fingerprint biometrics

Principles of fingerprint biometrics

A fingerprint is made of a a number of ridges and valleys on the surface of the finger. Ridges are the upper skin layer segments of the finger and valleys are the lower segments. The ridges form so-called minutia points: ridge endings (where a ridge end) and ridge bifurcations (where a ridge splits in two). Many types of minutiae exist, including dots (very small ridges), islands (ridges slightly longer than dots, occupying a middle space between two temporarily divergent ridges), ponds or lakes (empty spaces between two temporarily divergent ridges), spurs (a notch protruding from a ridge), bridges (small ridges joining two longer adjacent ridges), and crossovers (two ridges which cross each other).

The uniqueness of a fingerprint can be determined by the pattern of ridges and furrows as well as the minutiae points. There are five basic fingerprint patterns: arch, tented arch, left loop, right loop and whorl. Loops make up 60% of all fingerprints, whorls account for 30%, and arches for 10%.

Fingerprints are usually considered to be unique, with no two fingers having the exact same dermal ridge characteristics.

How does fingerprint biometrics work

The main technologies used to capture the fingerprint image with sufficient detail are optical, silicon, and ultrasound.

There are two main algorithm families to recognize fingerprints:

Minutia matching compares specific details within the fingerprint ridges. At registration (also called enrollment), the minutia points are located, together with their relative positions to each other and their directions. At the matching stage, the fingerprint image is processed to extract its minutia points, which are then compared with the registered template.
Pattern matching compares the overall characteristics of the fingerprints, not only individual points. Fingerprint characteristics can include sub-areas of certain interest including ridge thickness, curvature, or density. During enrollment, small sections of the fingerprint and their relative distances are extracted from the fingerprint. Areas of interest are the area around a minutia point, areas with low curvature radius, and areas with unusual combinations of ridges.

Issues with fingerprint systems

The tip of the finger is a small area from which to take measurements, and ridge patterns can be affected by cuts, dirt, or even wear and tear. Acquiring high-quality images of distinctive fingerprint ridges and minutiae is complicated task.

People with no or few minutia points (surgeons as they often wash their hands with strong detergents, builders, people with special skin conditions) cannot enroll or use the system. The number of minutia points can be a limiting factor for security of the algorithm. Results can also be confused by false minutia points (areas of obfuscation that appear due to low-quality enrollment, imaging, or fingerprint ridge detail).

Note: There is some controversy over the uniqueness of fingerprints. The quality of partial prints is however the limiting factor. As the number of defining points of the fingerprint become smaller, the degree of certainty of identity declines. There have been a few well-documented cases of people being wrongly accused on the basis of partial fingerprints.

Benefits of fingerprint biometric systems

  • Easy to use
  • Cheap
  • Small size
  • Low power
  • Non-intrusive
  • Large database already available

Applications of fingerprint biometrics

Fingerprint sensors are best for devices such as cell phones, USB flash drives, notebook computers and other applications where price, size, cost and low power are key requirements. Fingerprint biometric systems are also used for law enforcement, background searches to screen job applicants, healthcare and welfare.

Hand biometrics

Principles of hand biometrics

An individual’s hand does not significantly change after a certain age. Unlike fingerprints, the human hand isn’t unique. Individual hand features are not descriptive enough for identification. However, hand biometric recognition systems are accurate for verification purposes when combining various individual features and measurements of fingers and hands.

How does hand biometrics work

Biometric hand recognition systems measure and analyze the overall structure, shape and porportions of the hand, e.g. length, width and thickness of hand, fingers and joints; characteristics of the skin surface such as creases and ridges. Some hand geometry biometrics systems measure up to 90 parameters.

As hand biometrics rely on hand and finger geometry, the system will also work with dirty hands. The only limitation is for people with severe arthristis who cannot spread their hands on the reader.

The user places the palm of his or her hand on the reader’s surface and aligns his or her hand with the guidance pegs which indicate the proper location of the fingers. The device checks its database for verification of the user. The process normally only takes a few seconds.

To enroll, the users places his or her hand palm down on the reader’s surface.

To prevent a mold or a cast of the hand from being used, some hand biometric systems will require the user to move their fingers. Also, hand thermography can be used to record the heat of the hand, or skin conductivity can be measured.

Benefits of hand biometric systems

  • Easy to use
  • Non intrusive
  • Small amount of data required to uniquely identify a user, so a large number of templates can be easily stored in a standalone device: Hand biometric systems will generally only require a template size of 10 bytes, which is much smaller than most other biometric technologies (fingerprint systems require 250 to 1,000 bytes and voice biometric systems require 1,500 to 3,000 bytes)
  • Low FTE (failure to enroll) rates

Weaknesses of hand biometric systems

  • Lack of accuracy, so it can only be used for verification
  • Size of the scanner
  • Fairly expensive, compared with fingerprint systems
  • Injuries to hands are fairly common and would prevent the hand biometric system from working properly

Applications of hand biometrics

Hand biometric systems are currently among the most widely used biometric technologies.

  • Time and attendance
  • Access to restricted areas and buildings: Hand biometric systems are currently used in appartment buildings, offices, airports, day care centers, welfare agencies, hospitals, and immigration facilities.

Palm vein biometric systems

Principles of palm vein biometrics

The pattern of blood veins is unique to every individual, even among identical twins. Palms have a broad and complicated vascular pattern and thus contain a wealth of differentiating features for personal identification. Furthermore, it will not vary during the person’s lifetime. It is a very secure method of authentication because this blood vein pattern lies under the skin. This makes it almost impossible for others to read or copy.

How does palm vein biometrics work

An individual’s vein pattern image is captured by radiating his/her hand with near-infrared rays. The reflection method illuminates the palm using an infrared ray and captures the light given off by the region after diffusion through the palm. The deoxidized hemoglobin in the in the vein vessels absorbs the infrared ray, thereby reducing the reflection rate and causing the veins to appear as a black pattern. This vein pattern is then verified against a preregistered pattern to authenticate the individual.

As veins are internal in the body and have a wealth of differentiating features, attempts to forge an identity are extremely difficult, thereby enabling a high level of security. In addition, the sensor of the palm vein device can only recognize the pattern if the deoxidized hemoglobin is actively flowing within the individual’s veins.

This sytem is not dangerous, a near infrared is a component of sunlight: there is no more exposure when scanning the hand than by walking outside in the sun.

How does palm vein biometrics compare with other biometric systems?

As palm veins are inside the hand, they are protected and this system is not susceptible to minor trauma, cuts, etc (conversely to some fingerprint systems). Also, this sytem doesn’t have the same potential civil libery issues as face recognition techniques: Your face face can be scanned without you being aware of it, but your palm vein remain hidden.

Benefits of palm vein biometric systems

  • Difficult to forge
  • Contactless, hygienic and non-invasive
  • Highly accurate
  • Capable of 1:1 and 1:many matching

Applications of palm vein biometrics

  • Security systems: physical admission into secured areas with oor lock and integrated building security systems
  • Log-in control: network or PC access
  • Healthcare: ID verification for medical equipment, electronic record management
  • Banking and financial services: access to ATM, kiosks, vault
  • The Fujitsu palm vein contactless biometrics system is already used by Bank of Tokyo-Mitsubishi (BTM) in Japan.

Iris biometrics

Principles of iris biometrics

The iris is the elastic, pigmented, connective tissue that controls the pupil. The iris is formed in early life in a process called morphogenesis. Once fully formed, the texture is stable throughout life. It is the only internal human organ visible from the outside and is protected by the cornea. The iris of the eye has a unique pattern, from eye to eye and person to person.

How does iris biometrics work

An iris scan will analyze over 200 points of the iris, such as rings, furrows, freckles, the corona and will compare it it a previously recorded template.

Glasses, contact lenses, and even eye surgery does not change the characteristics of the iris.

To prevent an image / photo of the iris from being used instead of a real “live” eye, iris scanning systems will vary the light and check that the pupil dilates or contracts.

Benefits of retina biometric systems

  • Highly accurate: There is no known case of a false acceptance for iris recognition
  • Not intrusive and hygienic – no physical contact required

Weaknesses of retina biometric systems

The user must hold still while the scan is taking place

Applications of iris biometrics

Applications include: Identity cards and passports, border control and other Government programmes, prison security, database access and computer login, hospital security, schools, aviation security, controlling access to restricted areas, buildings and homes.

Retina biometrics

Principles of retina biometrics

The blood vessels at the back of the eye have a unique pattern, from eye to eye and person to person.

How does retina biometrics work

Retina scans require that the person removes their glasses, place their eye close to the scanner, stare at a specific point, and remain still, and focus on a specified location for approximately 10 to 15 seconds while the scan is completed. A retinal scan involves the use of a low-intensity coherent light source, which is projected onto the retina to illuminate the blood vessels which are then photographed and analysed. A coupler is used to read the blood vessel patterns.

A retina scan cannot be faked as it is currently impossible to forge a human retina. Furthermore, the retina of a deceased person decays too rapidly to be used to deceive a retinal scan.

A retinal scan has an error rate of 1 in 10,000,000, compared to fingerprint identification error being sometimes as high as 1 in 500.

Issues with retina systems

Enrollment and scanning are intrusive and slow.

Benefits of retina biometric systems

Highly accurate

Applications of retina biometrics

  • Retina biometrics systems are suited for environments requiring maximum security, such as Government, military and banking.
  • Retina biometric systems have been in use for military applications since the early seventies

Face biometrics

Principles of face biometrics

The dimensions, proportions and physical attributes of a person’s face are unique.

How does face biometrics work

Biometric facial recognition systems will measure and analyze the overall structure, shape and porportions of the face: Distance between the eyes, nose, mouth, and jaw edges; upper outlines of the eye sockets, the sides of the mouth, the location of the nose and eyes, the area surrounding the cheekbones.

At enrolment, several pictures are taken of the user’s face, with slightly different angles and facial expressions, to allow for more accurate matching. For verification and identification, the user stands in front of the camera for a few seconds, and the scan is compared with the template previously recorded.

To prevent an image / photo of the face or a mask from being used, face biometric systems will require the user to smile, blink, or nod their head. Also, facial thermography can be used to record the heat of the face (which won’t be affected by a mask).

The main facial recognition methods are: feature analysis, neural network, eigenfaces, and automatic face processing.

Benefits of face biometric systems

Not intrusive, can be done from a distance, even without the user being aware of it (for instance when scanning the entrance to a bank or a high security area).

Weaknesses of face biometric systems

  • Face biometric systems are more suited for authentication than for identification purposes, as it is easy to change the proportion of one’s face by wearing a mask, a nose extension, etc.
  • User perceptions / civil liberty: Most people are incomfortable with having their picture taken.

Applications of face biometrics

Access to restricted areas and buildings, banks, embassies, military sites, airports, law enforcement.

Voice biometrics

Principles of voice biometrics

Our voices are unique to each person (including twins), and cannot be exactly replicated.

How does voice biometrics work

Speech includes two components: a physiological component (the voice tract) and a behavioural component (the accent). It is almost impossible to imitate anyone’s voice perfectly. Voice recognition systems can discriminate between two very similar voices, including twins.

The voiceprint generated upon enrolment is characterised by the vocal tract, which is a unique a physiological trait. A cold does not affect the vocal tract, so there will be no adverse affect on accuracy levels. Only extreme vocal conditions such as laryngitis will prevent the user from using the system.

During enrollment, the user is prompted to repeat a short passphrase or a sequence of numbers. Voice recognition can utilize various audio capture device (microphones, telephones and PC microphones). The performance of voice recognition systems may vary depending on the quality of the audio signal.

To prevents the risk of unauthorised access via tape recordings, the user is asked to repeat random phrases.

Benefits of voice biometric systems

  • Ability to use existing telephones
  • Can be automated, and coupled with speech recognition systems
  • Low perceived invasiveness

Weaknesses of voice biometric systems

High false non-matching rates

Applications of voice biometrics

Voice biometric systems are mostly used for telephony-based applications. Voice verification is used for government, healthcare, call centers, electronic commerce, financial services, customer authentication for service calls, and for house arrest and probation-related authentication.

DNA biometrics

Principles of DNA biometrics

Humans have 23 pairs of chromosomes containing their DNA blueprint. One member of each chromosomal pair comes from their mother, the other comes from their father. Every cell in a human body contains a copy of this DNA. The large majority of DNA does not differ from person to person, but 0.10 percent of a person’s entire genome would be unique to each indiviual. This represents 3 million base pairs of DNA.

Genes make up 5 percent of the human genome. The other 95 percent are non-coding sequences, (which used to be called junk DNA). In non-coding regions there are identical repeat sequences of DNA, which can be repeated anywhere from one to 30 times in a row. These regions are called variable number tandem repeats (VNTRs). The number of tandem repeats at specific places (called loci) on chromosomes varies between individuals. For any given VNTR loci in an individual’s DNA, there will be a certain number of repeats. The higher number of loci are analysed, the smaller the probability to find two unrelated individuals with the same DNA profile.

DNA profiling determines the number of VNTR repeats at a number of distinctive loci, and use it to create an individual’s DNA profile. The main steps to create a DNA profile are: isolate the DNA (from a sample such as blood, saliva, hair, semen, or tissue), cut the DNA up into shorter fragments containing known VNTR areas, sort the DNA fragments by size, and compare the DNA fragments in different samples.

Benefits of DNA biometric systems

Accurate: the chance of 2 individuals sharing the same DNA profile is less than one in a hundred billion with 26 different bands studied.

Weaknesses of DNA biometric systems

  • DNA matching is not done in real-time
  • Intrusive: a physical sample must be taken, while other biometric systems only use an image or a recording
  • Civil liberty issues and public perception

Applications of DNA biometrics

DNA evidence has been used in courts of law since 1985 to prove guilt or innocence. It is also used for paternity testing, identification of missing or dead people.

Signature biometrics

How does a signature biometric system work

Biometric signature recognition systems will measure and analyze the physical activity of signing, such as the stroke order, the pressure applied and the speed. Some systems may also compare visual images of signatures, but the core of a signature biometric system is behavioral, i.e. how it is signed rather than visual, i.e. the image of the signature.

Benefits of signature biometric systems

  • While it is easy to copy the image of a signature, it is extremely difficult to mimick the behavior of signing
  • Low False Acceptance Rates (FAR)
  • People are used to sign documents, so signature recognition systems are not perceived to be invasive

Weaknesses of signature biometric systems

People may not always sign in a consistent manner

Applications of face biometrics

Access to documents, contract / agreement execution, acknowledgement of goods or services received, banking services

Multimodal biometrics

Access control biometrics provide improved security

Biometric products provide improved security over traditional electronic access control methods such as RFID tags, electronic keypads and some mechanical locks. They ensure that the authorized user is present in order for access to take place. The user’s authorized card or password pin cannot be stolen or lost to gain access.

Common physical biometrics includes fingerprints, hand or palm geometry, retina, iris, or facial characteristics, whereas behavioural characteristics include signature, voice (which also has a physical component), keystroke pattern, and gait. While some technologies have gained more acceptance then others, it is beyond doubt that the field of access control biometrics has gained a measure of acceptance.

Multimodal biometrics use a combination of different biometric recognition technologies

In order for the biometrics to be ultra-secure and to provide more-than-average accuracy, more then one form of biometric identification is required. Hence the need arises for the use of multimodal biometrics. This uses a combination of different biometric recognition technologies.

In certain situations, the user might find one form of biometric identification is not exact enough for identification. This can be the case with fingerprints, where at least 10% of the population have worn, cut or unrecognizable prints.

Multimodal biometric technology uses more then one biometric identifier to compare the identity of the person. Therefore in the case of a system using say three technologies i.e. face mimic and voice. If one of the technologies is unable to identify, the system can still use the other two to accurately identify against. Multimodal technologies have been in use commercially since 1998.

2B1:1 and 1:N matching

A biometric recognition system can be used in two different modes: identification (1:N matching) or verification (1:1 matching).

Identification is the process of trying to find out a person’s identity by comparing the person who is present against a biometric pattern/template database. The system would have been pre-programmed with biometric pattern or template of multiple individuals. During the enrolment stage, a biometric would have been processed, stored and encrypted, for each individual.

A pattern / template that is going to be identified is going to be matched against every known template, yielding either a score or distance describing the similarity between the pattern and the template. The system assigns the pattern to the person with the most similar biometric template. To prevent impostor patterns (in this case all patterns of persons not known by the system) from being correctly identified, the similarity has to exceed a certain level. If this level is not reached, the pattern is rejected.

With verification, a person’s identity is known and therefore claimed a priority to search against. The pattern that is being verified is compared with the person’s individual template only. Similar to identification, it is checked whether the similarity between pattern and template is sufficient enough to provide access to the secured system or area.

Multimodal biometrics in terms of FAR & FRR

Biometric systems use scores (also called weights) to express the similarity between a pattern and a biometric template. The higher the score, the higher the similarity is between them. As described in the previous section, access to the system is granted only, if the score for an authorized individual (identification) or the person that the pattern is verified against (verification) is higher then a certain threshold. In theory, authorized user scores (scores of patterns from persons known by the system) should always be higher than the scores of impostors. If this was true, a single threshold, that separates the two groups of scores, could be used to differ between clients and impostors. This unfortunately is not the reality for real world biometric systems. In some cases, impostor patterns can generate scores that are higher than the scores of an authorized user’s patterns (FAR or false acceptance rate). For this reason when the classification threshold is chosen some classification errors may occur. For example you may configure the threshold with a high setting, which will reject all impostor patterns that exceed this limit. As a result no patterns are falsely accepted by the system. But on the other hand the authorised user patterns with scores lower than the highest impostor scores are also falsely rejected. The opposite scenario would be to configure a low threshold that ensures no client patterns are falsely rejected. However, this would than allow a certain percentage of impostor patterns to be falsely accepted. If you choose the threshold somewhere between those two points, both false rejections and rejections false acceptances occur. This creates an access control environment which is obviously not ideal for high security installations.

The benefits of multimodal biometrics

By using more then one means of biometric identification, the multimodal biometric identifier can retain high threshold recognition settings. The system administrator can then decide the level of security he/she requires. For a high security site, they might require all three biometric identifiers to recognise the person or for a lower security site, only one or two of the three. With this methodology, the probability of accepting an impostor is greatly reduced.