6.1 Data Security

Security vs Privacy vs Integrity

Data Security

Definition: Protection of data from unauthorised access, use, disclosure, disruption, modification, or destruction.

Key aspects:

Confidentiality: Only authorised users can access data
Availability: Data is accessible when needed
Access control: Who can do what with data

Focus: Protecting data from threats (external and internal)

Data Privacy

Definition: The right of individuals to control how their personal information is collected, used, shared, and stored.

Key aspects:

Consent: Individuals must agree to data collection
Purpose limitation: Data used only for stated purpose
Data minimisation: Only collect what’s necessary
Individual rights: Access, correction, deletion

Focus: Ethical and legal handling of personal information

Data Integrity

Definition: The accuracy, consistency, and trustworthiness of data throughout its lifecycle.

Key aspects:

Accuracy: Data correctly represents real-world values
Consistency: Data remains unchanged during processing/transfer
Validity: Data conforms to defined rules and formats
Completeness: No missing or corrupted data

Focus: Maintaining correctness and reliability of data

Comparison

Aspect	Security	Privacy	Integrity
Primary concern	Unauthorised access	Personal data rights	Data correctness
Threats	Hackers, malware	Misuse of personal data	Corruption, errors
Protection methods	Encryption, firewalls	Consent, anonymisation	Validation, checksums
Example	Stopping hacker stealing data	Asking permission to use email	Ensuring bank balance is correct

Relationship Between Them

                    ┌─────────────────┐
                    │    Security     │
                    │  (protects all  │
                    │     data)       │
                    └────────┬────────┘
                             │
              ┌──────────────┼──────────────┐
              │              │              │
              ↓              ↓              ↓
    ┌─────────────┐  ┌─────────────┐  ┌─────────────┐
    │   Privacy   │  │  Integrity  │  │   Other     │
    │(personal data│  │(all data)   │  │  aspects    │
    └─────────────┘  └─────────────┘  └─────────────┘

Example: Medical records

Security: Prevent unauthorised access to records
Privacy: Patient controls who sees their records
Integrity: Ensure dosage information is correct

Need for Security of Data and Computer Systems

Why Secure Both?

Data Security alone is insufficient because data exists within computer systems.

Computer System Security protects the infrastructure:

Hardware (servers, workstations, network devices)
Software (OS, applications)
Network connections

Data Security protects the information itself:

Files and databases
Communications
Backups

Interdependence

Computer System Security         Data Security
    ┌──────────────┐             ┌──────────────┐
    │ Firewalls    │◄───────────►│ Encryption   │
    │ Antivirus    │◄───────────►│ Access rights│
    │ User accounts│◄───────────►│ Backups      │
    │ Updates      │◄───────────►│ Validation   │
    └──────────────┘             └──────────────┘

If system security fails:

Hackers can bypass data security measures
Malware can corrupt or steal data
System crash can destroy data

If data security fails:

Even secure systems may leak information
Insiders can misuse access
Data corruption may go undetected

Real-World Example: Online Banking

Security Layer	What it protects
Computer System	Banking servers, network infrastructure
Data Security	Account balances, transaction records
Both needed	If server hacked → data stolen; if data corrupted → wrong balances

Security Measures for Computer Systems

User Accounts

Purpose: Identify and authenticate users accessing the system.

Types:

Administrator/root: Full system access
Standard user: Limited access (cannot install software, change system settings)
Guest: Very limited, temporary access

Best practices:

Principle of least privilege (users get minimum access needed)
Regular review of accounts (remove unused)
Disable default accounts
Strong password policies

Passwords

Purpose: Authenticate user identity (something you know).

Characteristics of strong passwords:

Minimum length (8+ characters)
Mix of uppercase, lowercase, numbers, symbols
Not dictionary words
Not personal information (birthdays, names)
Changed regularly
Not reused across different systems

Password storage best practices:

Never store plaintext passwords
Use salting + hashing (bcrypt, PBKDF2, Argon2)
Rate limiting on login attempts

Weaknesses:

Can be guessed or brute-forced
Users choose weak passwords
Can be stolen (phishing, keyloggers)
Written down or shared

Authentication Techniques

Something you know:

Passwords, PINs, security questions

Something you have:

Smart cards, tokens, phone (2FA)
Hardware security keys (YubiKey)

Something you are (Biometrics):

Fingerprint scanners
Facial recognition
Iris scans
Voice recognition
Retina scans
Hand geometry

Somewhere you are:

Geolocation, IP address checking

Multi-Factor Authentication (MFA):
Combines two or more methods (e.g., password + fingerprint + phone)

Digital Signatures

Purpose: Verify authenticity and integrity of digital messages/documents.

How they work:

Sender:
1. Hash document → digest
2. Encrypt digest with private key → signature
3. Send document + signature

Receiver:
1. Hash received document → digest2
2. Decrypt signature with sender's public key → digest1
3. If digest1 = digest2, document authentic and unchanged

Properties:

Authentication: Proves sender’s identity
Non-repudiation: Sender cannot deny sending
Integrity: Detects any changes

Applications:

Software distribution (signed drivers)
Email signing (PGP, S/MIME)
Digital contracts
Code signing certificates

Biometrics

Purpose: Authenticate using unique physical characteristics.

Common types:

Type	How it works	Accuracy	Uses
Fingerprint	Scans ridge patterns	High	Phones, laptops, door access
Facial recognition	Analyses face geometry	Medium-High	Phones, surveillance
Iris scan	Analyses iris patterns	Very high	High security areas
Voice recognition	Analyses voice patterns	Medium	Phone banking, smart speakers
Retina scan	Scans blood vessel pattern	Very high	Military, research
Hand geometry	Measures hand shape	Medium	Building access

Advantages:

Cannot be forgotten or lost
Difficult to forge
Convenient (nothing to carry)

Disadvantages:

Cannot be changed if compromised
Privacy concerns
False acceptance/rejection rates
Cost of hardware
Health/sanitation concerns (fingerprint scanners)

Firewall

Purpose: Monitors and controls incoming/outgoing network traffic based on security rules.

Types:

Type	Description	Example
Packet filtering	Examines packets; allows/blocks based on IP, port, protocol	Basic router firewall
Stateful inspection	Tracks connection state; more sophisticated	Enterprise firewalls
Application-level gateway (proxy)	Filters specific applications	Web proxy
Next-generation firewall	Deep packet inspection, intrusion prevention	Modern corporate firewalls

What firewalls can block:

Unauthorised incoming connections
Specific ports/services
Certain IP addresses/ranges
Suspicious outgoing traffic (malware calling home)

Where firewalls are used:

Personal: Software firewall on PC (Windows Firewall)
Network: Hardware firewall at network perimeter
Cloud: Virtual firewalls in cloud environments

Rule example:

ALLOW TCP 192.168.1.0/24 ANY 80,443  (web access for LAN)
DENY TCP ANY ANY 22                   (block SSH from outside)
ALLOW UDP 10.0.0.1 53 ANY             (allow DNS from specific server)

Anti-Virus Software

Purpose: Detects, prevents, and removes malicious software.

Detection methods:

Method	Description	Advantages	Disadvantages
Signature-based	Matches files against known virus patterns	Accurate for known threats	Misses new viruses; needs updates
Heuristic analysis	Looks for suspicious behaviour	Can detect new variants	False positives
Behavioural monitoring	Monitors program actions	Detects zero-day attacks	Resource intensive
Sandboxing	Runs suspicious code in isolated environment	Safe analysis	Slows execution

Features:

Real-time scanning (on file access)
Scheduled scans
Email scanning
Web protection
Quarantine management
Automatic updates

Limitations:

Cannot protect against all threats
Needs constant updates
May slow system
Can be disabled by sophisticated malware

Anti-Spyware

Purpose: Specifically targets spyware (software that secretly monitors user activity).

What spyware does:

Records keystrokes (keyloggers)
Captures screenshots
Steals login credentials
Monitors browsing habits
Collects personal information

Anti-spyware features:

Browser cleanup (remove toolbars, extensions)
Tracking cookie removal
Browser hijacker detection
Real-time protection

Often combined with antivirus (modern security suites include both)

Encryption

Purpose: Converts readable data (plaintext) into unreadable format (ciphertext) using an algorithm and key.

Types:

Type	Description	Example	Use case
Symmetric	Same key for encryption/decryption	AES, DES, 3DES	File encryption, disk encryption
Asymmetric	Public/private key pair	RSA, ECC	SSL/TLS, email encryption

Applications:

Application	What is encrypted	Purpose
Full disk encryption	Entire hard drive	Protect data if device stolen
File/folder encryption	Specific files	Additional security for sensitive data
Email encryption	Email content	Confidential communication
HTTPS	Web traffic	Secure browsing
VPN	All network traffic	Privacy on public networks
Database encryption	Database contents	Protect stored data

Example: HTTPS encryption

User ────[encrypted]────> Website
        (cannot read)
Hacker ──[sees gibberish]─>

Threats to Computer and Data Security

Malware (Malicious Software)

Definition: Software designed to harm, exploit, or otherwise compromise a computer system.

Virus

Characteristics:

Self-replicating code that attaches to clean files
Spreads when infected file is executed
Requires human action to spread (opening file, running program)
Can corrupt data, damage system, steal information

Types:

File infector: Attaches to executable files
Boot sector: Infects boot sector of disks
Macro virus: In documents (Word, Excel macros)
Polymorphic virus: Changes code to avoid detection

Infection vectors:

Email attachments
Downloaded files
Infected software
Removable drives (USB)

Spyware

Characteristics:

Secretly monitors user activity
Collects and transmits information without consent
Often installed with other software (bundling)
Runs in background, hard to detect

What spyware collects:

Keystrokes (keyloggers)
Browsing history
Login credentials
Credit card numbers
Personal documents

Signs of infection:

Slow performance
Unexpected pop-ups
Changed browser homepage
New toolbars

Hackers

Definition: Individuals who attempt to gain unauthorised access to computer systems.

Types:

Type	Description	Motivation
White hat	Ethical hackers; find vulnerabilities to help	Improve security
Black hat	Malicious hackers; break in illegally	Profit, damage, notoriety
Grey hat	Between; may break in but not maliciously	Personal challenge
Script kiddie	Uses existing tools without deep knowledge	Thrill seeking
Hacktivist	Hacks for political/social causes	Promote agenda
State-sponsored	Employed by governments	Espionage, warfare

Common hacking techniques:

Password cracking (brute force, dictionary attacks)
Exploiting unpatched vulnerabilities
Social engineering
Man-in-the-middle attacks
SQL injection
Cross-site scripting (XSS)

Phishing

Definition: Fraudulent attempt to obtain sensitive information by disguising as trustworthy entity.

How it works:

Attacker sends communication (email, text, message)
Appears to be from legitimate organisation (bank, PayPal, HMRC)
Creates urgency (account suspended, unusual activity)
Contains link to fake website
Victim enters credentials on fake site
Attacker steals information

Types of phishing:

Type	Description	Example
Email phishing	Mass emails to many targets	“Your account needs verification”
Spear phishing	Targeted at specific individual	“HR: Update your details”
Whaling	Targets high-profile executives	“CEO: Urgent wire transfer”
Smishing	SMS/text message phishing	“Your package delivery failed”
Vishing	Voice call phishing	Fake tech support calls

Red flags:

Generic greetings (“Dear Customer”)
Spelling/grammar errors
Suspicious sender email address
Urgent/threatening language
Hover over links (shows different URL)
Requests for personal information

Pharming

Definition: Redirecting users from legitimate website to fake one without their knowledge.

How it works:

Method 1: DNS poisoning

Attacker compromises DNS server
Changes legitimate domain (bank.com) to point to fake IP
All users of that DNS server redirected to fake site
Browser shows correct URL but wrong site

Method 2: Hosts file modification

Malware modifies computer’s hosts file
bank.com now points to fake IP
User types correct URL but goes to fake site

Comparison with phishing:

Phishing: User tricked into clicking fake link
Pharming: User types correct address but still redirected

Protection:

Use secure DNS servers
Keep hosts file protected
Look for HTTPS (green padlock)
Check certificates

Other Threats

Threat	Description
Denial of Service (DoS)	Overwhelms system with traffic, making it unavailable
Distributed DoS (DDoS)	DoS from many sources simultaneously
Man-in-the-Middle	Attacker intercepts communication between two parties
Ransomware	Encrypts data and demands payment for decryption
Trojan	Malware disguised as legitimate software
Worm	Self-replicating malware that spreads automatically
Rootkit	Hides malware deep in system (often kernel level)
Keylogger	Records keystrokes
Zero-day exploit	Attacks unknown, unpatched vulnerability

Methods to Restrict Risks

Risk Restriction Strategies

1. Prevention

Stop threats before they occur
Examples: Firewalls, access controls, user training

2. Detection

Identify threats that occur
Examples: Intrusion detection systems, log monitoring

3. Response

Act when threats detected
Examples: Incident response plans, isolation of infected systems

4. Recovery

Restore after successful attack
Examples: Backups, disaster recovery plans

Practical Risk Restriction Measures

Measure	What it prevents
Regular software updates	Known vulnerabilities
Strong password policy	Unauthorised access
Multi-factor authentication	Stolen credentials
Employee training	Phishing, social engineering
Principle of least privilege	Insider threats, malware spread
Network segmentation	Lateral movement of attackers
Regular backups	Ransomware, data loss
Incident response plan	Minimise damage when breached
Security audits	Identify weaknesses
Physical security	Theft of devices

Security Methods to Protect Data

Encryption (for Data)

Data at rest:

Full disk encryption (BitLocker, FileVault)
File/folder encryption (EFS, VeraCrypt)
Database encryption (TDE)
Removable media encryption (encrypted USB)

Data in transit:

TLS/SSL (HTTPS)
VPN
SSH
Encrypted email (PGP)

Data in use:

Memory encryption (limited)
Homomorphic encryption (emerging)

Access Rights / Permissions

Purpose: Control who can do what with data.

Access levels:

Level	Permissions	Example
Read	View file contents	Users reading documentation
Write	Modify file contents	Editors updating documents
Execute	Run program	Users running application
Delete	Remove file	Administrators cleaning up
Full control	All permissions + change permissions	System administrators

Implementation methods:

Discretionary Access Control (DAC):

Owners control their files
Windows file permissions
Linux chmod

Mandatory Access Control (MAC):

System-enforced policies
SELinux, AppArmor
Multi-level security

Role-Based Access Control (RBAC):

Permissions assigned to roles
Users assigned to roles
Common in organisations

Access Control Lists (ACL):

File: payroll.xlsx
User A: Read
User B: Read/Write
Group HR: Read/Write
Group Everyone: No access

User authentication:

Username/password
Biometrics
Security tokens

Benefits of access rights:

Prevents unauthorised access
Limits damage from compromised accounts
Enforces separation of duties
Supports data confidentiality

6.2 Data Integrity

Data Validation vs Data Verification

Data Validation

Definition: Checking that data meets certain rules or constraints before it is accepted into a system.

Purpose: Prevent invalid data from entering the system.

When it occurs: At data entry time.

Focus: Is the data reasonable and in the correct format?

Data Verification

Definition: Checking that data matches the original source after it has been entered or transferred.

Purpose: Ensure data has been entered or transferred correctly.

When it occurs: After data entry or during/after transfer.

Focus: Is the data accurate compared to the source?

Comparison

Aspect	Validation	Verification
Purpose	Check data is sensible/valid	Check data matches source
Timing	Before acceptance	After entry/transfer
Prevents	Invalid data entry	Transcription/transfer errors
Example	Age cannot be 200	Re-enter email to confirm
Automation	Usually automatic	Can be manual or automatic

Data Validation Methods

Range Check

Definition: Checks if data falls within a specified range of acceptable values.

Examples:

Age must be between 0 and 130
Temperature between -50°C and +50°C
Exam mark between 0 and 100

Code example (validation logic):

IF age >= 0 AND age <= 130 THEN
    accept
ELSE
    error "Age must be between 0 and 130"
ENDIF

Format Check

Definition: Checks if data follows a specified pattern or template.

Examples:

Email must contain @ and .
Postcode must follow specific pattern (e.g., LLNN NLL for UK)
Phone number must have 11 digits
Date must be DD/MM/YYYY

Regular expression examples:

Email: ^[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}$
UK Postcode: ^[A-Z]{1,2}[0-9][A-Z0-9]? ?[0-9][A-Z]{2}$

Length Check

Definition: Checks that data has the required number of characters.

Examples:

Password must be at least 8 characters
Username maximum 20 characters
Postcode exactly 8 characters (including space)
Telephone number between 10-15 digits

Code example:

IF LENGTH(password) >= 8 THEN
    accept
ELSE
    error "Password too short"
ENDIF

Presence Check

Definition: Checks that data has actually been entered (not left blank).

Examples:

Name field cannot be empty
Email address required
Terms and conditions must be accepted

Code example:

IF field IS NOT EMPTY THEN
    accept
ELSE
    error "This field is required"
ENDIF

Existence Check

Definition: Checks that a value exists in a reference table or database.

Examples:

Department code exists in departments table
Product ID exists in products database
Country code is valid

Code example:

SELECT COUNT(*) FROM departments WHERE dept_code = input
IF count > 0 THEN
    accept
ELSE
    error "Invalid department code"
ENDIF

Limit Check

Definition: Similar to range check but checks only one boundary (upper or lower limit).

Examples:

Stock level cannot go below 0 (lower limit)
Maximum order quantity 100 (upper limit)
Minimum order value £10 (lower limit)

Code example:

IF quantity <= 100 THEN
    accept
ELSE
    error "Maximum order quantity is 100"
ENDIF

Check Digit

Definition: A calculated digit appended to a number to detect errors in data entry/transmission.

How it works:

Original number has check digit calculated using algorithm
Check digit appended to number
When number entered, algorithm recalculates check digit
If calculated ≠ appended, error detected

Common algorithms:

Modulo 10 (ISBN-13 example):

Number: 978034098382
Positions: 1  2  3  4  5  6  7  8  9  10 11 12
Multiply:  1  3  1  3  1  3  1  3  1  3  1  3
Result:    9 21  8  0  3  0  9 24  8  0  3  6
Sum = 91
91 mod 10 = 1
Check digit = (10 - 1) mod 10 = 9
Complete number: 9780340983829

ISBN-10 example:

Number: 034098382
Multiply each digit by position (10 down to 1):
0×10 + 3×9 + 4×8 + 0×7 + 9×6 + 8×5 + 3×4 + 8×3 + 2×2
= 0 + 27 + 32 + 0 + 54 + 40 + 12 + 24 + 4 = 193
193 mod 11 = 6
Check digit = 11 - 6 = 5
Complete: 0340983825

Credit Card (Luhn algorithm):

Double every second digit from right
If doubling results in >9, add digits (e.g., 16 → 1+6=7)
Sum all digits
Check digit makes total divisible by 10

Applications:

ISBN (books)
Credit card numbers
National ID numbers
Barcodes (EAN-13, UPC)

Data Verification Methods

During Data Entry

Visual Check / Double Entry

Visual Check (Screen Check):

User reviews entered data on screen before final submission
Compares with original source document
Manual process, prone to human error
Example: Confirmation screen showing entered details

Double Entry:

Data entered twice, preferably by different people
System compares both entries
If they match, data accepted
If different, error flagged
Very effective for critical data

Example: Creating new user account

First entry: email@example.com
Second entry: email@example.com
System compares → match → accepted

Applications:

Creating passwords (enter twice)
Financial data entry
Research data input
Medical records

During Data Transfer

Parity Check

Purpose: Detect errors during data transmission.

Simple (Single) Parity Check:

Even parity: Number of 1s in data + parity bit = even
Odd parity: Number of 1s in data + parity bit = odd

Example (even parity):

Data: 1011001 (4 ones → even already)
Parity bit: 0
Transmitted: 10110010

Data: 1101011 (5 ones → odd)
Parity bit: 1 (to make even)
Transmitted: 11010111

Error detection:

Received: 10110011 (5 ones → odd, but even parity expected)
Error detected!

Limitations:

Can only detect odd number of bit errors
Cannot correct errors (only detect)
If two bits flip, parity remains same → error undetected

Block Parity Checks

Purpose: Improve error detection by organising data into blocks.

How it works:

Data arranged in rows and columns
Parity calculated for each row AND each column

Example 4×4 block:
Data:   1 0 1 1
        0 1 0 1
        1 1 0 0
        0 0 1 0

Row parity:   1 0 1 1 | 1 (row parity)
              0 1 0 1 | 0
              1 1 0 0 | 0
              0 0 1 0 | 1
Column parity:0 0 0 0

Transmit all data + row parity + column parity

Advantages:

Can locate which bit is in error (intersection of bad row and bad column)
Better detection than single parity

Checksum

Purpose: Verify integrity of data block using calculated sum.

How it works:

Simple checksum:

Divide data into fixed-size blocks (e.g., 16-bit words)
Sum all blocks (ignoring overflow)
Transmit sum with data
Receiver recalculates sum and compares

Example:

Data: 10101100 11010011 01110101
Blocks:   172      211      117
Sum = 172 + 211 + 117 = 500 (or use 8-bit wrap)
Transmit data + checksum (500)

Cyclic Redundancy Check (CRC):

More sophisticated than simple sum
Treats data as polynomial
Divides by predetermined polynomial
Remainder is CRC value
Very good at detecting common errors
Used in network protocols (Ethernet, Wi-Fi)

MD5/SHA hashes:

Cryptographic hash functions
Produce fixed-size hash from any data
Very low collision probability
Used for file integrity verification

Applications:

Network packet integrity (TCP checksum)
File download verification (MD5/SHA)
Storage systems (RAID)
Version control (Git uses SHA-1)

Verification Methods Comparison

Method	Detects	Can correct?	Overhead	Use case
Visual check	Transcription errors	Manual	Time	Critical data entry
Double entry	Typing errors	No (re-enter)	2× entry	Passwords, financial
Single parity	Odd bit errors	No	1 bit	Simple serial communication
Block parity	Multiple errors; locates single	Yes (single bit)	More bits	Memory (ECC RAM)
Checksum	Many errors	No	16/32 bits	Network packets
CRC	Very good detection	No	16/32 bits	Storage, networks
Hash (MD5/SHA)	Excellent detection	No	128-512 bits	File verification

Summary Checklist for Assessment Objectives

AO1 (Knowledge) – You should be able to:

✓ Define security, privacy, integrity and explain differences
✓ Explain need for both system and data security
✓ List security measures (user accounts, passwords, biometrics, firewalls, antivirus, etc.)
✓ Describe threats (malware types, hackers, phishing, pharming)
✓ Define validation and verification
✓ List validation methods (range, format, length, presence, existence, limit, check digit)
✓ List verification methods (visual, double entry, parity, checksum)

AO2 (Application) – You should be able to:

✓ Apply appropriate security measures for given scenarios
✓ Identify threats from described situations
✓ Recommend risk restriction methods
✓ Apply validation checks to data
✓ Calculate parity bits
✓ Verify using checksums
✓ Apply check digit algorithms

AO3 (Design/Evaluation) – You should be able to:

✓ Evaluate security requirements for different systems
✓ Compare security measures and justify choices
✓ Assess threat impact and prioritise protections
✓ Design validation rules for data entry forms
✓ Evaluate verification methods for different situations
✓ Judge effectiveness of security implementations