← VCE Data Analytics U4O2

Data integrity characteristic: authenticity

Data is authentic when it genuinely comes from the source it claims and has not been forged or spoofed. Verifying its origin shows it can be trusted.

Part of: VCE Data Analytics - U4O2 - Cyber Security: Data Security — Module 21, ACARA Digital Technologies Years 9–10 — Acquiring and Validating Data — Module 81, QCE Digital Solutions Unit 4 — Complex Digital Data Exchange Problems and Solution Requirements — Module 65

Understanding Data integrity characteristic: authenticity in VCE Data Analytics U4O2

What it does: Checking a digital signature against the sender's public key is a way of verifying origin, which supports authenticity. Accepting data only from known trusted sources protects authenticity by rejecting data of unknown origin. A digital signature (e.g. ECDSA) can be checked to prove who created the data. A file name is easy to fake. Verifying origin builds trust in the data. Being up to date is timeliness, a different characteristic.

Common mistakes: The trusted list must only hold verified sources. An anonymous source can't be verified, so data from it can't be treated as authentic. Line 1 should list only trusted sources such as "HR" and "Payroll". Origin is verified when the sender matches the real source. Using != would call mismatched (possibly spoofed) senders verified. It should be if sender == real:.

Class: _____________________ · Name: _____________________ · Date: _________

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This module's key terms are also in a printable crossword (Modules 1–25) and word search (Modules 1–43).

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Learning

Duo

Data is authentic when it genuinely comes from the source it claims.

FalseTrue

Matches

IF data looks correct THEN trust it

↓

Data that looks correct may still be forged. Authenticity needs the origin to be verified, not just the appearance checked.

Applying

Meanings

Term

Authenticity

Meaning

Data is authentic when it genuinely comes from the source it claims and has not been forged or spoofed. Verifying its origin shows it can be trusted.

Practice

IF source IS trusted AND signature IS valid THEN

Testing

Gaps

IF sender = trustedSource accept(data)

Check Answer

Spots

1trusted = ["HR", "Anonymous"]

2source = "HR"

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Quick Questions

1. Data is authentic when it genuinely comes from the source it claims.

A. False

B. True ✓

Authenticity is about origin: the data really comes from the source it says it does and has not been forged.

2. An email says it is from the ATO, but the sender address was faked to look like the ATO. Which describes this data?

A. Not authentic: the source is spoofed ✓

B. Authentic: it names a trusted source

Claiming to come from a trusted source is not enough. Spoofed data pretends to come from a source it did not.

3. Which step best verifies the origin of a file?

A. Check its digital signature against the sender's public key ✓

B. Check that the file name looks professional

A digital signature (e.g. ECDSA) can be checked to prove who created the data. A file name is easy to fake.

4. A data set is accurate, so it must also be authentic.

A. True

B. False ✓

Data can have correct values but still come from an unverified or forged source. Authenticity and accuracy are separate.

5. Which is an example of forged data?

A. A fake invoice made to look like it came from a real supplier ✓

B. A real invoice with a typing error in the total

Forged data is deliberately made to look like it came from a trusted source. A typing error is an accuracy problem, not forgery.

Match the Pairs

Authenticity → Data is authentic when it genuinely comes from the source it claims and has not been forged or spoofed.

Spoofed sender address → Forged data that pretends to come from a trusted source, so it is not authentic.

Verifying the origin of a file by checking it was signed by the trusted sender → verify_signature(file, sender_public_key)

Only accepting data from a trusted source on an approved list → IF source IN trusted_sources THEN accept ELSE reject

IF data looks correct THEN trust it → Data that looks correct may still be forged. Authenticity needs the origin to be verified, not just the appearance checked.

IF sender_name = "Payroll Team" THEN accept → A sender name can be spoofed. Trusting the name alone does not verify that the data genuinely came from the source.

Key Term

Authenticity

Data is authentic when it genuinely comes from the source it claims and has not been forged or spoofed. Verifying its origin shows it can be trusted.

Fill in the Blanks

1. IF sender = trustedSource THEN accept(data)

Hint: Type the keyword that introduces the action to run when the origin check is true

2. IF NOT sigValid THEN reject(data)

Hint: Type the action name that refuses data whose signature cannot be verified

3. IF sender != trustedSource THEN flag(data)

Hint: Type the operator that checks the sender is NOT equal to the trusted source

4. valid ← verifySignature(data, sig)

Hint: Type the assignment symbol that stores the verification result in the variable

5. IF domainOk AND sigValid THEN accept(data)

Hint: Type the logical operator that requires both origin checks to pass

Spot the Error

Question 1

A trusted = ["HR", "Anonymous"]

B source = "HR"

C if source in trusted:

D print("Authentic")

Line A — The trusted list must only hold verified sources. An anonymous source can't be verified, so data from it can't be treated as authentic. Line 1 should list only trusted sources such as "HR" and "Payroll".

Question 2

A sender = "bank.com.au"

B real = "bank.com.au"

C if sender != real:

D print("Origin verified")

Line C — Origin is verified when the sender matches the real source. Using != would call mismatched (possibly spoofed) senders verified. It should be if sender == real:.

Question 3

A ok = check_size(file)

B if ok:

C print("Authentic")

Line A — Authenticity depends on verifying where the data came from. Checking file size says nothing about the origin and can't detect a forged file. It should be ok = check_signature(file).

Question 4

A email = get_email()

B domain = email.domain

C if domain in trusted:

D reject(email)

E else:

F quarantine(email)

Line D — Data from a trusted source is treated as authentic and should be accepted. Rejecting it throws away genuine data. Line 4 should be accept(email), and untrusted email goes to quarantine.

Question 5

A if sender_verified:

B trust = "high"

C else:

D trust = "high"

Line D — If the sender is not verified, the data may be forged or spoofed, so trust should be low. Giving unverified data high trust defeats authenticity. Line 4 should be trust = "low".

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