Biometric authentication

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Quick Questions

Shade in the A or B circle for each question.

1. Which of these is an example of biometric authentication?

A Unlocking a phone with a fingerprint scan

B Unlocking a phone with a 4-digit PIN

2. What does a face recognition system do to check who you are?

A Compares your face to a stored template

B Asks you to recall a secret phrase

3. A false accept happens when a biometric system...

A Blocks a person who is authorised

B Lets in a person who is not authorised

4. A false reject happens when a biometric system...

A Blocks the real, authorised user

B Lets an attacker in by mistake

5. Which trait is a behavioural biometric?

A Fingerprint ridges

B Voice pattern or typing rhythm

Match the Pairs

Draw a line connecting each item on the left to its match on the right.

Left column		Right column
1method = "fingerprint scan"		ABiometric data is stored as an unencrypted raw image. If the database is breached, the traits cannot be reset like a password, creating a serious privacy risk.
2result = "false reject"		Bstore(encrypt(face_template))
3A false accept is a serious security risk because an impostor's biometric is wrongly matched to a real user.		CA physical biometric trait: the unique pattern of ridges on a finger is matched against a stored template to prove identity.
4Biometric data is sensitive personal information, so templates should be stored encrypted rather than as raw images.		Dif match_score >= threshold: grant_access()
5biometric_data = "face_scan.jpg" # stored as plain text, unprotected		EThe system wrongly refuses a genuine, authorised user because their biometric does not match closely enough.
6authentication = "voice recognition uses something you know"		FVoice recognition is a biometric, so it is something you are, not something you know. Passwords and PINs are the something you know factor.

Definitions

biometric authentication

Fill in the Blanks

Complete each line of code by filling in the missing parts.

__ match_score >= 80 THEN grant_access()

A false ______ lets an impostor in

A false ______ blocks the real user

Biometric data is _________ information

match ← compare(scan, ________)

Spot the Error

Shade in the letter of the line that contains an error.

Question 1

A scan ← captureFingerprint()

B template ← getTemplate(user)

C score ← match(scan, scan)

D IF score >= threshold THEN

E grant access

Question 2

A image ← captureVoice()

B features ← extract(image)

C score ← match(features, saved)

D IF score >= threshold THEN

E unlock phone

Question 3

A threshold ← 0.95

B IF score <= threshold THEN

C DISPLAY 'Access granted'

D ELSE

E DISPLAY 'Access denied'

Question 4

A accepted ← 3

B imposters ← 100

C FAR ← accepted * imposters

D DISPLAY FAR

Question 5

A rejected ← 0

B IF owner AND score >= min THEN

C rejected ← rejected + 1

D ENDIF

Answer Key

Biometric authentication

Section A: Quick Questions

A — Unlocking a phone with a fingerprint scan

A — Compares your face to a stored template

B — Lets in a person who is not authorised

A — Blocks the real, authorised user

B — Voice pattern or typing rhythm

Section B: Match the Pairs

method = "fingerprint scan" → A physical biometric trait: the unique pattern of ridges on a finger is matched against a stored template to prove identity.

result = "false reject" → The system wrongly refuses a genuine, authorised user because their biometric does not match closely enough.

A false accept is a serious security risk because an impostor's biometric is wrongly matched to a real user. → if match_score >= threshold: grant_access()

Biometric data is sensitive personal information, so templates should be stored encrypted rather than as raw images. → store(encrypt(face_template))

biometric_data = "face_scan.jpg" # stored as plain text, unprotected → Biometric data is stored as an unencrypted raw image. If the database is breached, the traits cannot be reset like a password, creating a serious privacy risk.

authentication = "voice recognition uses something you know" → Voice recognition is a biometric, so it is something you are, not something you know. Passwords and PINs are the something you know factor.

Section C: Definitions

biometric authentication — Proves who you are using a physical or behavioural trait, such as a fingerprint, face or voice, that is matched against stored data. It can wrongly accept or reject users.

Section D: Fill in the Blanks

IF match_score >= 80 THEN grant_access()

A false accept lets an impostor in

A false reject blocks the real user

Biometric data is sensitive information

match ← compare(scan, template)

Section E: Spot the Error

C — The new scan is compared with itself, so it would always match. It must be compared with the stored template: match(scan, template).

A — Face recognition needs a picture of the face. The program should call captureFace(), not record a voice.

B — The check is reversed. It would grant access to poor matches and reject good ones. It should be score >= threshold.

C — The false accept rate is a proportion. It is the number of imposters wrongly accepted divided by the number of imposter attempts, so it needs / not *.

B — A false reject is when the real owner is turned away. That happens when the score is below the minimum (score < min), not at or above it.