Cybersecurity, Privacy, Ethics and Technology Governance

Introduction

Retail has become a technology-intensive sector in which payments, customer identification, inventory, logistics, pricing, marketing, workforce management and customer service depend on interconnected digital systems. This interdependence creates strategic value but also concentrates risk. A compromised point-of-sale terminal can expose payment credentials; a misconfigured cloud database can reveal customer records; an opaque recommendation model can discriminate against customer groups; and an unavailable ordering platform can interrupt revenue and damage trust.

Cybersecurity, privacy, ethics and technology governance are therefore not merely technical or legal concerns. They are management responsibilities connected to customer trust, business continuity, brand equity, regulatory compliance and competitive advantage. Retail managers must understand how controls operate, why risks arise, how decisions should be governed and how security and privacy can be incorporated into technology strategy.

This chapter presents an integrated approach to protecting retail payments, customer data, operations and algorithmic decisions. It distinguishes cybersecurity from privacy, explains access control and resilience, introduces risk and governance frameworks, and applies these ideas through an illustrative retail case.

Learning Objectives

After studying this chapter, the learner should be able to:

1. Explain the relationship between cybersecurity, privacy, ethics and technology governance in retail.
2. Identify threats to payment systems, customer data, connected devices and retail operations.
3. Apply confidentiality, integrity and availability principles to retail systems.
4. Design appropriate identity, access-control, encryption, monitoring and resilience measures.
5. Evaluate privacy risks and apply privacy-by-design and data-governance principles.
6. Assess ethical risks in personalization, surveillance, pricing and algorithmic decision-making.
7. Use risk-based governance to prioritize controls, accountability and investment.
8. Recommend improvements for a retail organization facing a cyber or technology-governance challenge.

1. The Retail Technology Risk Environment

A modern retailer operates an ecosystem rather than an isolated information system. Typical components include e-commerce platforms, mobile applications, payment gateways, point-of-sale systems, loyalty databases, warehouse-management systems, supplier portals, customer-service tools, workforce applications, cameras, electronic shelf labels, Internet-of-Things devices and cloud services. Application programming interfaces connect many of these components to external partners.

The ecosystem creates several forms of exposure:

• External exposure: websites, mobile applications, APIs and payment interfaces are accessible to customers and partners.
• Third-party exposure: payment processors, delivery firms, marketing platforms and cloud providers may process retail data.
• Human exposure: employees, contractors and customers may make errors or fall victim to social engineering.
• Operational exposure: a cyberattack can stop checkout, replenishment, fulfilment or delivery.
• Data exposure: retailers hold identity, contact, transaction, behavioural, location and sometimes financial information.
• Algorithmic exposure: automated systems may produce unfair, inaccurate or unexplained outcomes.

A useful risk expression is:

Likelihood represents the estimated probability or frequency of an adverse event, while impact represents the resulting financial, operational, legal, safety or reputational consequence. This is a prioritization model rather than a precise physical law. Organizations may use ordinal scales, monetary estimates or probabilistic models, but they should define scales consistently. Risk is not eliminated by technology alone; it is reduced through controls, informed decisions and continuous oversight.

2. Core Security Principles

2.1 The CIA triad

The classical security model consists of:

• Confidentiality: information is disclosed only to authorized people, systems or processes.
• Integrity: information and systems remain accurate, complete and protected from unauthorized alteration.
• Availability: authorized users can access systems and information when required.

For example, encryption of customer records supports confidentiality, transaction validation supports integrity, and redundant payment infrastructure supports availability. Retail security must address all three. A system that is confidential but unavailable cannot process sales; a highly available system that produces altered prices is also unsafe.

2.2 Authenticity, accountability and non-repudiation

Authenticity establishes that a user, device, message or transaction is genuine. Accountability connects actions to responsible identities through logging and monitoring. Non-repudiation provides evidence that an action occurred and was associated with a particular party, although its legal effect depends on jurisdiction, evidence quality and organizational procedures.

These principles are important in refunds, price changes, supplier-bank-detail changes, privileged administration and employee access to customer records.

2.3 Defence in depth and zero trust

Defence in depth uses multiple layers of protection: secure design, identity controls, network segmentation, endpoint protection, encryption, monitoring, backups and incident response. No individual control is assumed to be perfect.

Zero trust is a security approach based on the principle that access should not be trusted automatically merely because a user or device is inside a corporate network. Access decisions should consider identity, device condition, location, requested resource, context and risk. Zero trust does not mean refusing all access; it means continuously validating access and limiting it to what is necessary.

3. Threats and Vulnerabilities in Retail

A threat is a potential cause of harm, while a vulnerability is a weakness that a threat can exploit. A control is a safeguard that reduces likelihood, impact or both.

Important retail threats include:

Vulnerabilities may arise from unpatched software, weak passwords, excessive privileges, insecure defaults, poor network segmentation, unsupported devices, inadequate testing, missing logs or unclear ownership. A mature program searches for systemic weaknesses rather than blaming individuals after an incident.

4. Identity and Access Management

Identity and access management (IAM) determines who or what may access which resource, under what conditions and for what purpose. Its lifecycle includes identity proofing, account creation, authentication, authorization, review, suspension and deletion.

4.1 Authentication

Authentication verifies identity. Common factors are:

1. Knowledge: password or PIN.
2. Possession: security key, authenticator application or registered device.
3. Inherence: biometric characteristic.

Multi-factor authentication (MFA) combines independent factors. A password plus a second code is stronger than a password alone, although phishing-resistant methods such as hardware security keys generally provide stronger protection than easily intercepted codes.

Passwords should be unique, resistant to guessing, protected against automated attacks and stored using an appropriate salted password-hashing method rather than reversible encryption. Shared accounts weaken accountability and should be avoided except where technically unavoidable and carefully controlled.

4.2 Authorization models

• Role-based access control (RBAC): permissions are assigned to roles such as cashier, store manager, buyer or security administrator.
• Attribute-based access control (ABAC): decisions use attributes such as department, device status, location, time and data sensitivity.
• Rule-based control: explicit rules determine whether access is permitted.
• Privileged access management (PAM): high-risk administrative access is restricted, time-limited, monitored and often approved separately.

The principle of least privilege grants only the access necessary for a legitimate task. Separation of duties prevents one person from completing a sensitive process alone, such as creating a supplier and approving payment. Access reviews should be risk-based and should occur when roles change, when people leave and at defined intervals.

4.3 Access-control decision sequence

A practical access decision asks:

1. Who is requesting access?
2. What resource is requested?
3. What action is requested?
4. Is the identity strongly authenticated?
5. Is the device and session trustworthy?
6. Is there a legitimate business need?
7. Is the action logged and reviewable?

This approach is particularly important for customer-service staff who may need limited access to an order but not to complete payment credentials or unrelated customer histories.

5. Protecting Payments and Sensitive Data

Payment security requires cooperation among the retailer, payment service provider, banks, device manufacturers and customers. Retailers should minimize the systems that handle sensitive payment data. Tokenization replaces a payment credential with a surrogate token that is less useful if stolen. Point-to-point encryption protects data during transmission from a payment device to an approved endpoint, but it does not remove the need for secure devices, access control and monitoring.

Retailers should maintain an accurate data-flow map showing where payment and personal data are collected, transmitted, processed, stored and deleted. The payment-card security standard applicable to the organization should be treated as a baseline, not as a substitute for broader cyber-risk management.

5.1 Encryption and key management

Encryption transforms readable information, called plaintext, into ciphertext using a key. Strong encryption is undermined by poor key management. Keys require controlled generation, storage, rotation, backup, revocation and destruction. Access to decryption keys should be more restricted than access to ordinary application data.

Data should be protected both in transit and at rest. Sensitive data should not be copied into logs, test environments or analytics stores without a defined need. Masking, redaction, pseudonymization and tokenization reduce exposure, although pseudonymized data may still be personal data if re-identification remains reasonably possible.

5.2 Data classification and retention

A classification scheme might include public, internal, confidential and highly restricted information. Classification should determine handling, encryption, access, retention and disposal requirements. Retaining data indefinitely increases the consequences of a breach and creates unnecessary privacy risk. Retention periods should reflect legal duties, operational needs and documented business purposes.

6. Privacy and Responsible Data Governance

Privacy concerns the appropriate collection, use, sharing and control of information relating to identifiable or identifiable individuals. Privacy is broader than secrecy. A customer may object to a legitimate collection because it is excessive, unexpected, manipulative or used for a different purpose.

6.1 Privacy principles

Although legal requirements vary by jurisdiction, widely recognized principles include:

• lawfulness, fairness and transparency;
• purpose limitation;
• data minimization;
• accuracy;
• storage limitation;
• integrity and confidentiality; and
• accountability.

A retailer should be able to answer: What data is collected? Why is it needed? What legal or organizational basis supports the processing? Who receives it? How long is it retained? How can an individual exercise applicable rights? What safeguards are used?

Consent is not a universal solution. It should be informed, specific, freely given and capable of withdrawal where consent is the relevant basis. A retailer should not make an unnecessary loyalty benefit practically compulsory by bundling unrelated data uses into a single unclear choice.

6.2 Privacy by design

Privacy by design integrates privacy into system architecture rather than adding notices after implementation. Examples include:

• collecting an age range rather than a full birth date when exact age is unnecessary;
• using tokens instead of raw payment identifiers;
• separating identity data from analytical data;
• applying default retention limits;
• providing granular marketing choices; and
• testing whether staff can access data beyond their role.

A privacy impact assessment is useful when introducing facial recognition, location tracking, extensive profiling, biometric systems, children’s services or large-scale behavioural analytics. It should identify purposes, data flows, affected groups, risks, mitigations and residual risk owners.

6.3 Data governance

Data governance assigns decision rights and accountability. Typical roles include data owner, data steward, privacy officer, security officer, system owner and business process owner. Governance should cover data quality, definitions, lineage, access, retention, third-party sharing, incident response and individual requests.

A data inventory or record of processing should be maintained as a living management instrument, not merely prepared for an audit. It should connect data assets to systems, purposes, owners, controls and legal or contractual obligations.

7. Ethics in Retail Technology

Legal compliance is necessary but insufficient. Ethical analysis asks whether a practice is fair, respectful, explainable, proportionate and consistent with the values of the organization and society.

7.1 Personalization and surveillance

Personalized recommendations may improve relevance, but extensive tracking can reduce autonomy. Retailers should consider whether customers reasonably expect the collection, whether the benefit is proportionate to the intrusion and whether vulnerable groups may be affected differently. Facial recognition in stores raises questions of necessity, accuracy, consent, notice, retention and the possibility of chilling ordinary behaviour.

7.2 Dynamic pricing and discrimination

Dynamic pricing can respond to demand and inventory, but it may be ethically problematic if prices vary based on protected characteristics, exploit vulnerability or are presented deceptively. A pricing model should be tested for disparate outcomes, unstable behaviour and prohibited variables or proxies. Fairness is not achieved merely by removing an explicitly protected field because other variables may reproduce its effect.

7.3 Algorithmic accountability

Algorithmic systems should have:

• a clearly defined purpose;
• an identified accountable owner;
• documented data sources and limitations;
• validation before deployment;
• monitoring after deployment;
• human review for high-impact decisions;
• an appeal or correction mechanism; and
• controlled retirement when performance or legitimacy declines.

Explainability should be appropriate to the audience. A customer needs a comprehensible reason for an adverse decision; a technical team may need feature-level diagnostics; an auditor may need data lineage, test evidence and change records.

7.4 Generative AI and automated assistants

Generative AI can support customer service, product descriptions, fraud investigation and workforce assistance. Risks include fabricated answers, disclosure of confidential prompts or data, intellectual-property concerns, insecure plug-ins and automation bias. Controls should include approved use cases, data restrictions, human oversight, output testing, logging, vendor review and a prohibition on treating generated text as authoritative without verification.

8. Technology Governance and Risk Management

Technology governance is the system by which an organization directs, controls and evaluates technology. It links technology decisions to strategy, risk appetite, compliance, resources and stakeholder interests.

8.1 Governance structure

The board or governing body sets oversight expectations and risk appetite. Senior management allocates resources and accepts or mitigates risk. A technology or security committee coordinates priorities. The chief information security officer, privacy leader and technology executives provide expertise, while business owners remain accountable for the processes and data they use. Internal audit provides independent assurance.

Governance should distinguish:

• Policy: mandatory organizational direction.
• Standard: specific required control or technical expectation.
• Procedure: detailed operational steps.
• Guideline: recommended practice where context permits.
• Evidence: records demonstrating that controls operate.

8.2 Frameworks

Organizations commonly combine several complementary frameworks rather than selecting one universal model:

Framework adoption should not become a checkbox exercise. The organization must define scope, ownership, measurable outcomes, exceptions and evidence.

8.3 Risk treatment

For each material risk, management may:

1. avoid the activity;
2. reduce likelihood or impact through controls;
3. transfer part of the risk through contracts or insurance; or
4. accept the residual risk through an authorized decision.

Acceptance should specify the risk, rationale, duration, owner, compensating controls and review date. “No known issue” is not equivalent to informed acceptance.

Useful performance indicators include MFA coverage, privileged-account review completion, critical-patch age, backup restoration success, time to detect, time to contain, unresolved high-risk findings, privacy-request completion and vendor-assessment coverage. Metrics should support decisions rather than reward superficial activity. For example, counting security alerts without measuring meaningful response may encourage noise rather than resilience.

9. Resilience, Incident Response and Recovery

Security aims to prevent incidents, but resilience assumes that some incidents will occur. Resilience is the capacity to continue important functions, respond effectively and recover while learning.

Business impact analysis identifies critical processes, dependencies and acceptable disruption. Two important planning measures are:

• Recovery time objective (RTO): the maximum targeted time to restore a service after disruption.
• Recovery point objective (RPO): the maximum targeted period of data loss measured in time.

For example, an RTO of two hours means the service target is restoration within two hours; an RPO of fifteen minutes means recovery should lose no more than approximately fifteen minutes of transactions. These are targets, not guarantees, and must be supported by architecture, contracts, staffing and tested procedures.

Incident response typically includes preparation, detection and analysis, containment, eradication, recovery and post-incident improvement. Evidence preservation, legal notification analysis, customer communication and coordination with suppliers are essential. Backups should be protected from the same attack as production systems, separated appropriately, monitored and tested through restoration exercises.

10. Third-Party and Supply-Chain Governance

Retailers often depend on external providers for payments, cloud hosting, delivery, marketing, analytics and managed security. Vendor risk management should begin before contracting and continue throughout the relationship.

Assessment should consider data access, system criticality, subcontractors, security practices, incident notification, resilience, audit rights, data location, deletion, exit support and concentration risk. Contracts should define responsibilities clearly. A vendor certification may provide useful evidence but does not eliminate the retailer’s accountability for its own decisions and customer relationships.

Exit planning is frequently neglected. Retailers should know how data will be returned or deleted, how services will continue during transition, whether formats are portable and whether a supplier failure would create unacceptable concentration risk.

11. Illustrative Case: Northstar Market’s Loyalty and Checkout Transformation

Background

Northstar Market, a fictional regional retailer, introduced a mobile loyalty application, self-checkout, personalized offers and cloud-based analytics. The program connected point-of-sale systems, a loyalty database, an advertising platform and a third-party analytics provider.

Problem

After a rapid expansion, an employee reported that customer-service agents could search loyalty records using broad name and phone-number queries. A security review also found that an old service account had access to transaction exports, MFA was not enabled for all administrators and the analytics provider retained data longer than the business required. The recommendation engine produced fewer offers for customers in certain postcodes, but no fairness review had been performed.

Analysis

The situation involved several linked risks. Excessive access threatened confidentiality and accountability. The dormant service account created an attack path. Long retention increased breach impact and weakened purpose limitation. The postcode pattern might reflect legitimate commercial factors, but it could also act as a proxy for socioeconomic or protected characteristics. The retailer had treated deployment as a technical project rather than a governed business change.

Approach and solution

Northstar established a cross-functional governance group including security, privacy, legal, marketing, store operations, technology and customer experience. It completed a data-flow inventory and classified loyalty and transaction data. The retailer then:

1. implemented role-based access with masked fields and customer-service purpose restrictions;
2. removed dormant accounts and required phishing-resistant MFA for privileged users;
3. rotated service credentials and placed sensitive secrets in managed storage;
4. reduced analytics retention and prohibited secondary use without approval;
5. separated direct identifiers from analytical datasets;
6. assessed the recommendation model for performance and disparate outcomes;
7. introduced human review and a customer-support route for disputed offers;
8. required the analytics provider to demonstrate deletion and incident-notification capability;
9. tested backup restoration and simulated a checkout outage; and
10. created quarterly reporting on access reviews, privacy findings, model performance and resilience tests.

Outcome

Northstar reduced unnecessary access, improved evidence of accountability and clarified data-sharing responsibilities. The fairness review showed that the postcode variable was not itself discriminatory in every use, but it produced materially different offer exposure for some customer groups. Marketing removed the variable from the high-impact targeting rule and introduced monitoring for outcome disparities. The exercise also revealed that security, privacy and ethical concerns were not independent: the same data architecture could create all three types of risk.

Learning points

The case demonstrates that governance must begin before deployment and continue after launch. It also shows why access control, privacy impact assessment, supplier management, algorithmic testing and operational resilience should be designed as an integrated control system. A successful technology program is not measured only by adoption or sales uplift; it must also preserve trust, rights, continuity and accountability.

12. Implementation Road Map for Retail Managers

A practical improvement program can proceed through the following sequence:

1. Establish scope and accountability: identify critical services, data owners, system owners and decision rights.
2. Map assets and data flows: include stores, cloud services, APIs, devices, partners and shadow systems.
3. Assess risk: evaluate threats, vulnerabilities, affected stakeholders, legal duties and business impact.
4. Prioritize foundational controls: MFA, least privilege, patching, secure configuration, segmentation, encryption, logging and tested backups.
5. Strengthen privacy governance: define purposes, retention, notices, rights handling and impact-assessment triggers.
6. Govern algorithms: document purpose, data, testing, monitoring, human oversight and appeal.
7. Manage suppliers: assess critical vendors, contract controls and plan exit options.
8. Exercise response and recovery: simulate ransomware, payment disruption, data breach and model failure.
9. Measure and improve: use meaningful indicators, independent assurance and lessons from incidents and near misses.

Challenges and Limitations

No framework guarantees security or ethical outcomes. Threats evolve, controls can fail and risk assessments depend on uncertain information. More monitoring can improve detection while increasing privacy intrusion. Strong authentication can create accessibility or operational challenges if poorly designed. Encryption protects data but complicates recovery and key management. Algorithmic fairness cannot be reduced to one universal metric because different fairness definitions may conflict and business context matters.

Retailers also face resource constraints, legacy systems and dependence on suppliers. Governance can become bureaucratic if every decision requires excessive approval. Conversely, speed without control can externalize risk to customers and employees. Effective governance is therefore proportionate, risk-based, evidence-driven and capable of adapting to new technology.

Contemporary Developments and Best Practices

Current retail practice is increasingly shaped by passkeys and phishing-resistant authentication, confidential computing, software bills of materials, continuous third-party monitoring, privacy-enhancing technologies, automated security operations and regulatory attention to artificial intelligence. These developments should be assessed by business purpose and risk rather than adopted as fashionable labels.

Best practice includes secure-by-design procurement, default data minimization, independent testing, meaningful customer communication, accessible consent and preference controls, strong supplier contracts, regular access recertification, tested recovery, board-level reporting and a culture in which employees can report weaknesses without fear of blame. The strategic objective is not perfect prevention; it is trustworthy, resilient and accountable retail innovation.

Chapter Summary

Retail technology creates value through connected payments, data, automation and analytics, but connectivity also creates cyber, privacy, operational and ethical risk. The CIA triad provides a foundation for confidentiality, integrity and availability, while authenticity and accountability strengthen transaction trust. Defence in depth, zero-trust principles, MFA, least privilege, separation of duties, encryption, tokenization, logging and tested backups are core controls.

Privacy requires purposeful collection, minimization, transparency, appropriate retention and accountability. Privacy by design embeds these principles in architecture and processes. Ethical governance extends beyond legal compliance to fairness, autonomy, explainability, proportionality and human oversight, especially for personalization, surveillance, pricing and AI.

Technology governance assigns decision rights, risk ownership and assurance responsibilities. Frameworks such as the NIST Cybersecurity Framework, ISO/IEC 27001, COBIT, privacy-management approaches and PCI DSS can be combined according to organizational needs. Resilience requires business-impact analysis, RTO and RPO targets, incident response and tested restoration. Finally, third-party governance and continuous improvement are essential because retail risk crosses organizational boundaries.

Key Terms

Access control: Rules and mechanisms that determine who or what may use a resource.

Accountability: The ability to associate actions with responsible identities and decisions.

Authentication: Verification of an identity or system.

Authorization: Determination of permitted actions after authentication.

Confidentiality: Protection against unauthorized disclosure.

Data minimization: Collection and use of only the data necessary for a defined purpose.

Defence in depth: Use of multiple complementary security layers.

Encryption: Transformation of readable data into protected ciphertext using a key.

Integrity: Protection of information and systems against unauthorized or inaccurate alteration.

Least privilege: Granting only the access needed for a legitimate task.

Multi-factor authentication: Authentication using two or more independent factors.

Privacy by design: Incorporating privacy protections into systems and processes from the outset.

Recovery point objective: Maximum targeted period of data loss after disruption.

Recovery time objective: Maximum targeted time for restoring a service.

Resilience: Capacity to withstand, respond to and recover from disruption.

Risk: The combination of the likelihood and impact of an adverse event.

Tokenization: Replacement of sensitive data with a less sensitive surrogate token.

Technology governance: Direction, control and evaluation of technology-related decisions and risks.

Zero trust: An approach that continuously validates access rather than trusting network location by default.

Review Questions

Short Answer Questions

1. Define confidentiality, integrity and availability in the context of retail systems.
2. What is the principle of least privilege?
3. Distinguish privacy from cybersecurity.
4. What are RTO and RPO?
5. Why is multi-factor authentication important for privileged accounts?

Long Answer Questions

1. Explain how a retail organization can implement defence in depth across payment and e-commerce systems.
2. Discuss the role of privacy by design in a customer-loyalty application.
3. Compare RBAC and ABAC and recommend contexts in which each may be appropriate.
4. Explain how technology governance connects board oversight, business ownership and technical controls.
5. Evaluate the ethical risks of personalized pricing and algorithmic recommendations.

Analytical / Application Questions

1. A retailer discovers that a third-party analytics provider retains identifiable transaction data indefinitely. Analyze the risks and propose a remediation plan.
2. Design an incident-response and recovery approach for a ransomware attack that disables store checkout and warehouse systems.
3. A recommendation model provides substantially fewer promotions to customers in one geographic area. Develop an investigation and governance process that addresses accuracy, fairness, privacy and customer appeal.

Multiple Choice Questions with Answers

Question 1

Which principle requires retail information to remain accurate and protected from unauthorized alteration?

A. Confidentiality

B. Integrity

C. Availability

D. Non-repudiation

Correct Answer: B. Integrity

Question 2

Which control most directly limits an employee to the permissions necessary for a specific job?

A. Least privilege

B. Data portability

C. Purpose limitation

D. Tokenization

Correct Answer: A. Least privilege

Question 3

What does an RPO specify?

A. The maximum time allowed to restore a service

B. The number of employees required for recovery

C. The maximum targeted period of data loss

D. The maximum number of failed login attempts

Correct Answer: C. The maximum targeted period of data loss

Question 4

Which practice replaces a payment identifier with a surrogate value?

A. Hashing

B. Tokenization

C. Segmentation

D. Pseudonym-free storage

Correct Answer: B. Tokenization

Question 5

Which statement best describes zero trust?

A. All internal network users are trusted automatically

B. Only external users require authentication

C. Access is continuously evaluated rather than trusted by location alone

D. Security controls are unnecessary after encryption

Correct Answer: C. Access is continuously evaluated rather than trusted by location alone

Question 6

Which privacy principle restricts collection to information needed for a defined purpose?

A. Data minimization

B. Non-repudiation

C. Availability

D. Separation of duties

Correct Answer: A. Data minimization

Question 7

Which measure is most appropriate for protecting highly privileged administrative access?

A. A shared password used by the whole IT team

B. Permanent unrestricted access

C. Privileged access management with MFA and monitoring

D. Disabling all audit logs

Correct Answer: C. Privileged access management with MFA and monitoring

Question 8

Why should algorithmic retail decisions have an accountable owner?

A. To ensure that no human can review the model

B. To connect decisions, monitoring and corrective action to responsibility

C. To eliminate the need for data-quality testing

D. To guarantee that every customer receives the same offer

Correct Answer: B. To connect decisions, monitoring and corrective action to responsibility

Question 9

Which activity best tests whether backups are useful during a disruption?

A. Counting the number of backup files

B. Checking whether backup storage is colorful

C. Performing a restoration exercise

D. Deleting older backups without review

Correct Answer: C. Performing a restoration exercise

Question 10

A retailer uses a customer’s full birth date when only an age category is needed. Which privacy-by-design improvement is most appropriate?

A. Collect additional demographic data

B. Replace the birth date with an age range

C. Retain the birth date indefinitely

D. Share the birth date with more vendors

Correct Answer: B. Replace the birth date with an age range