Unit 1: Introduction to Privacy
- Data Protection & Privacy Terminologies
- Data Protection Principles and Approaches to Privacy
- Code for Protection of Personal Information
- Information Life Cycle
- Data Security Threats and Mitigation
- Data Storage Security Issues in Cloud Computing
Data Protection & Privacy Terminologies
- Data Protection: Safeguarding data from unauthorized access and ensuring its confidentiality and integrity.
- Privacy: The right of individuals to control their personal information and keep it confidential.
Data Protection Principles and Approaches to Privacy
- Principles
- Collection Limitation: Limiting the gathering of personal data to what is necessary.
- Purpose Specification: Clearly stating the purpose for which data is collected.
- Data Minimization: Collecting only the data essential for the intended purpose.
- Accuracy: Ensuring that collected data is accurate and up-to-date.
- Storage Limitation: Storing data for only as long as necessary.
- Integrity and Confidentiality: Protecting data from unauthorized access or alteration.
- Accountability: Holding organizations responsible for complying with data protection principles.
- Approaches to Privacy
- Privacy by Design: Incorporating privacy measures into the development of systems and processes.
- Privacy by Default: Ensuring that privacy settings are automatically set to the most secure option.
Code for Protection of Personal Information
- Legal Codes
- Examples: GDPR (General Data Protection Regulation) in Europe, CCPA (California Consumer Privacy Act) in the United States.
- Purpose: Defining rules and obligations for organizations to protect individuals’ personal information.
Information Life Cycle
- Creation and Collection: Acquiring data from various sources.
- Processing: Analyzing, organizing, and storing data.
- Transmission: Sending data to different locations or recipients.
- Storage: Archiving data for future use.
- Deletion/Disposal: Permanently removing or destroying data.
Data Security Threats and Mitigation
- Threats
- Unauthorized Access: Individuals or entities gaining access to data without permission.
- Data Breach: Unauthorized disclosure of sensitive information.
- Malware: Software designed to harm or exploit systems.
- Phishing: Deceptive attempts to obtain sensitive information.
- Insider Threats: Risks posed by individuals within an organization.
- Mitigation
- Encryption: Protecting data by converting it into a secure code.
- Access Controls: Restricting access to authorized personnel.
- Regular Audits: Monitoring and reviewing security measures.
- Employee Training: Educating staff about security best practices.
- Incident Response Plans: Preparedness for responding to security incidents.
Data Storage Security Issues in Cloud Computing
- Challenges
- Data Location: Uncertainty about the physical location of stored data.
- Multi-Tenancy: Multiple users sharing the same cloud infrastructure.
- Data Transfer: Security risks during data transfer to and from the cloud.
- Solutions
- Encryption: Encrypting data before storing it in the cloud.
- Access Controls: Implementing robust access management policies.
- Compliance: Ensuring cloud providers comply with data protection regulations.
Unit 2: Data Protection Principles and Safeguards
- Data protection principles
- Subject access request Damage or distress
- Preventing direct marketing Automated decision-making
- Correcting inaccurate personal data
- Compensation, Exemptions & Complaints
- Big data
- CCTV & Data Sharing
- Online & apps Privacy by design
- Guidance Note on Protecting the Confidentiality of Personal Data
- Safeguarding Personal Information
- Using Personal Information on Websites and with Other Internet-related Technologies
- Privacy considerations for sensitive online information, including policies and notices, access, security, authentication identification, and data collection
- Data Privacy in online data collection, email, searches, online marketing and advertising, social media, online assurance, cloud computing, and mobile devices
Data protection principles
- Transparency: Individuals should be informed about the processing of their personal data.
- Purpose Limitation: Data should be collected for specified, explicit, and legitimate purposes.
- Data Minimization: Collect only the data necessary for the purpose.
- Accuracy: Keep personal data accurate and up to date.
- Storage Limitation: Store data for only as long as necessary.
- Integrity and Confidentiality: Ensure the security and confidentiality of the data.
- Accountability: Organizations are responsible for demonstrating compliance with data protection principles.
Subject Access Request Damage or Distress
- Subject Access Request (SAR)
- Definition: Individuals have the right to request access to their personal data.
- Example: A person requests information held about them by a company.
- Damage or Distress
- Definition: Individuals may claim compensation for damage or distress resulting from a data breach.
- Example: A data breach causes emotional distress to affected individuals.
Preventing Direct Marketing Automated Decision-Making
- Preventing Direct Marketing
- Definition: Individuals have the right to opt out of direct marketing communications.
- Example: Allowing users to unsubscribe from promotional emails.
- Automated Decision-Making
- Definition: Decisions made solely by automated processes without human involvement.
- Example: An algorithm making credit decisions based on personal data.
Correcting Inaccurate Personal Data
- Data Accuracy
- Definition: Individuals have the right to rectify inaccurate personal data.
- Example: A person updates their address information with a service provider.
Compensation, Exemptions & Complaints
- Compensation
- Definition: Individuals may claim compensation for damages resulting from a data breach.
- Example: Legal action against a company for financial losses due to a data breach.
- Exemptions
- Definition: Certain data protection regulations may have exemptions for specific situations.
- Example: National security concerns may justify exemptions in certain cases.
- Complaints
- Definition: Individuals have the right to file complaints with regulatory authorities.
- Example: Submitting a complaint to a data protection authority about a privacy violation.
Big Data
- Big Data Analysis
- Definition: Processing large volumes of data to uncover patterns and insights.
- Example: Analyzing vast datasets for business intelligence or scientific research.
CCTV & Data Sharing
- CCTV
- Definition: Video surveillance using Closed-Circuit Television.
- Example: Monitoring public spaces for security purposes.
- Data Sharing
- Definition: Sharing personal data with third parties.
- Example: An organization sharing customer data with a partner for joint marketing efforts.
Online & Apps Privacy by Design
- Privacy by Design
- Definition: Integrating privacy measures into the design and development of systems.
- Example: Building privacy features into a mobile app during the development phase.
Guidance Note on Protecting the Confidentiality of Personal Data
- Guidance Note
- Definition: A document providing advice and recommendations on protecting personal data confidentiality.
- Example: A regulatory authority issuing guidance on secure handling of sensitive information.
Safeguarding Personal Information
- Security Measures
- Definition: Implementing measures to protect personal information from unauthorized access.
- Example: Using encryption and access controls to secure sensitive data.
Using Personal Information on Websites and with Other Internet-related Technologies
- Privacy Considerations
- Definition: Considering privacy implications when collecting and using personal information online.
- Example: Including a privacy policy on a website outlining data collection and usage practices.
Privacy considerations for sensitive online information, including policies and notices, access, security, authentication identification, and data collection
- Sensitive Information
- Definition: Information requiring special protection due to its sensitivity.
- Example: Health records or financial information.
Data Privacy in Online Data Collection, Email, Searches, Online Marketing and Advertising, Social Media, Online Assurance, Cloud Computing, and Mobile Devices
- Online Data Collection
- Definition: Gathering information from users on the internet.
- Example: E-commerce websites collecting customer details during the checkout process.
- Email, Searches, Online Marketing, and Advertising
- Definition: Privacy considerations for email communications, online searches, and targeted advertising.
- Example: Advertisers using cookies to display personalized ads to users.
- Social Media
- Definition: Privacy issues related to social networking platforms.
- Example: Users adjusting privacy settings on social media to control information visibility.
- Online Assurance, Cloud Computing, and Mobile Devices
- Definition: Ensuring privacy in online transactions, cloud storage, and mobile applications.
- Example: Implementing secure authentication for mobile banking apps to protect user data.
Unit 3: Data Privacy Management
- Data Privacy Management Controls & Plan
- Data Privacy Management Reference Model – ISTPA
- Data Protection in the Context of Police and Criminal Justice
- Cross Border data transfer
- Do Not Track Privacy Policy
- Developing Privacy Management Tools
- Information security practices for data privacy
- Developing a privacy management plan
- Rights of the Data Subject
- Documenting the privacy baseline of the organization
- Data processors and third-party vendor assessments
- Physical assessments; mergers, acquisitions, and divestitures
- Privacy threshold analysis; privacy impact assessments
- Privacy Monitoring and Incident Management (MIM)
- Auditing your privacy program; creating awareness of the organization’s privacy program; Compliance monitoring; handling information requests; and handling privacy incidents
Data Privacy Management Controls & Plan
- Data Privacy Management Controls
- Definition: Implementing measures to ensure the protection and proper handling of personal data.
- Example: Encryption, access controls, and regular audits as privacy management controls.
- Data Privacy Management Plan
- Definition: A strategic document outlining an organization’s approach to safeguarding and managing personal data.
- Example: Developing a comprehensive plan that includes data protection policies, procedures, and training programs.
Data Privacy Management Reference Model – ISTPA
- ISTPA (Information Security Technology Privacy Association) Reference Model
- Definition: A framework providing guidance on integrating privacy into information security.
- Example: Using ISTPA as a reference to develop a holistic approach to data privacy management.
Data Protection in the Context of Police and Criminal Justice
- Data Protection in Law Enforcement
- Definition: Special considerations and regulations regarding the processing of personal data in police and criminal justice activities.
- Example: Balancing law enforcement needs with individual privacy rights in criminal investigations.
Cross-Border Data Transfer
- Cross-Border Data Transfer
- Definition: The movement of personal data across international borders.
- Example: Transferring customer data from a European Union country to the United States for processing.
Do Not Track Privacy Policy
- Do Not Track
- Definition: A browser setting that signals websites not to track a user’s browsing activity.
- Example: Websites that respect the Do Not Track signal by refraining from collecting user data for targeted advertising.
Developing Privacy Management Tools
- Privacy Management Tools
- Definition: Software or tools designed to assist organizations in managing and protecting personal data.
- Example: Developing a customized data privacy dashboard to monitor compliance and incidents.
Information Security Practices for Data Privacy
- Information Security Practices
- Definition: Implementing security measures to protect personal data from unauthorized access and disclosure.
- Example: Using firewalls, intrusion detection systems, and secure coding practices to enhance information security.
Developing a Privacy Management Plan
- Privacy Management Plan Development
- Definition: Creating a comprehensive plan that outlines how an organization will handle and protect personal data.
- Example: Establishing policies, procedures, and employee training programs as part of the privacy management plan.
Rights of the Data Subject
- Data Subject Rights
- Definition: The rights individuals have regarding the processing of their personal data.
- Example: The right to access, rectify, and delete personal information held by organizations.
Documenting the Privacy Baseline of the Organization
- Privacy Baseline Documentation
- Definition: Recording the existing state of privacy practices within an organization.
- Example: Conducting a privacy audit and documenting current privacy policies and procedures.
Data Processors and Third-Party Vendor Assessments
- Third-Party Assessments
- Definition: Evaluating the privacy practices of data processors and external vendors.
- Example: Assessing the data protection measures of a cloud service provider before engaging their services.
Physical Assessments; Mergers, Acquisitions, and Divestitures
- Physical Assessments
- Definition: Evaluating physical security measures in place to protect personal data.
- Example: Conducting on-site inspections to assess physical security controls.
- Mergers, Acquisitions, and Divestitures
- Definition: Considering data privacy implications during organizational changes.
- Example: Assessing the privacy posture of a company being acquired to identify potential risks.
Privacy Threshold Analysis; Privacy Impact Assessments
- Privacy Threshold Analysis
- Definition: Determining whether a proposed project or system triggers the need for a comprehensive Privacy Impact Assessment (PIA).
- Example: Evaluating whether a new data processing system involves high-risk privacy considerations.
- Privacy Impact Assessments
- Definition: A systematic assessment of how a project or system impacts the privacy of individuals.
- Example: Conducting a PIA for a new customer relationship management system to assess privacy risks.
Privacy Monitoring and Incident Management (MIM)
- Privacy Monitoring
- Definition: Continuously monitoring systems and processes to detect and address privacy issues.
- Example: Implementing real-time monitoring tools to identify unauthorized access to sensitive data.
- Incident Management (MIM)
- Definition: Responding to and managing privacy incidents and breaches.
- Example: Establishing an incident response team to investigate and mitigate the impact of a data breach.
Auditing your Privacy Program; Creating Awareness of the Organization’s Privacy Program; Compliance Monitoring; Handling Information Requests; and Handling Privacy Incidents
- Auditing the Privacy Program
- Definition: Evaluating the effectiveness of an organization’s privacy management program through systematic reviews.
- Example: Conducting periodic audits to ensure compliance with data protection policies.
- Creating Awareness of the Organization’s Privacy Program
- Definition: Promoting awareness and understanding of data privacy policies and procedures among employees.
- Example: Conducting training sessions and awareness campaigns on data protection.
- Compliance Monitoring
- Definition: Ongoing monitoring to ensure adherence to privacy laws and regulations.
- Example: Regularly reviewing and updating policies to align with changes in data protection laws.
- Handling Information Requests
- Definition: Managing requests from individuals regarding their personal data.
- Example: Responding to a data subject access request and providing requested information in a timely manner.
- Handling Privacy Incidents
- Definition: Managing and responding to incidents that compromise the security of personal data.
- Example: Following an incident response plan to contain and mitigate the impact of a data breach.
Unit 4: Privacy Program Governance and Compliance and Legal Framework
- Privacy Organization and Relationship (POR)
- Privacy Policy and Processes (PPP)
- Regulatory Compliance Intelligence (RCI)
- Privacy legislation – applicability and interpretation
- Privacy Awareness and Training (PAT)
- Legal Framework for Data Protection, Security and Privacy Norms
Privacy Organization and Relationship (POR)
- Privacy Organization
- Definition: Establishing the organizational structure responsible for overseeing and managing privacy matters.
- Example: Appointing a Chief Privacy Officer (CPO) to lead the privacy team.
- Relationships
- Definition: Defining the relationships between different departments and stakeholders involved in privacy management.
- Example: Collaborating with legal, IT, and compliance teams to ensure a holistic approach to privacy.
Privacy Policy and Processes (PPP)
- Privacy Policy
- Definition: A document outlining an organization’s commitment to protecting personal data and the principles governing its use.
- Example: Publishing a privacy policy on a company website detailing data collection and processing practices.
- Processes
- Definition: Procedures and workflows designed to implement and enforce privacy policies.
- Example: Implementing a process for handling and responding to data subject access requests in line with privacy policy requirements.
Regulatory Compliance Intelligence (RCI)
- Regulatory Compliance Intelligence
- Definition: Monitoring and staying informed about changes in privacy laws and regulations.
- Example: Subscribing to regulatory updates and conducting regular compliance assessments to ensure adherence to evolving privacy standards.
Privacy Legislation – Applicability and Interpretation
- Applicability
- Definition: Determining the scope and reach of privacy legislation relevant to the organization.
- Example: Identifying whether international, national, or regional privacy laws apply based on the organization’s operations.
- Interpretation
- Definition: Understanding the legal requirements and implications of privacy legislation.
- Example: Seeking legal counsel to interpret and provide guidance on how specific privacy laws impact the organization.
Privacy Awareness and Training (PAT)
- Privacy Awareness
- Definition: Fostering an understanding and consciousness of privacy issues among employees.
- Example: Conducting regular awareness campaigns to educate employees about data protection best practices.
- Training
- Definition: Providing targeted education and training programs on privacy policies and procedures.
- Example: Conducting training sessions for employees to enhance their understanding of data protection laws and compliance requirements.
Legal Framework for Data Protection, Security, and Privacy Norms
- Legal Framework
- Definition: The set of laws, regulations, and legal principles that govern data protection, security, and privacy.
- Example: Understanding the legal framework that applies to the collection, processing, and storage of personal data.
- Privacy Norms
- Definition: Accepted standards and practices related to privacy in compliance with legal requirements.
- Example: Following industry-accepted privacy norms when designing systems or handling personal data.
Unit 5: Privacy in Cloud Computing and IoT
- Privacy in Cloud – Introduction to Privacy in Cloud Computing
- Cloud computing paradigm and privacy
- Challenges to privacy in cloud computing
- Privacy in IoT
- IoT Governance
- IoT Security & Privacy Issues
- IoT Privacy challenges
- IoT Privacy solutions
Privacy in Cloud – Introduction to Privacy in Cloud Computing
- Overview
- Definition: Introduction to the intersection of cloud computing and privacy considerations.
- Example: Understanding how cloud computing services impact the privacy of user data.
- Cloud Computing Paradigm and Privacy
- Definition: Exploring the fundamental principles of cloud computing and their implications for privacy.
- Example: Assessing the shared responsibility model in cloud computing and its impact on data privacy.
- Challenges to Privacy in Cloud Computing
- Definition: Identifying and addressing the privacy challenges associated with cloud computing.
- Example: Addressing concerns about data residency and jurisdiction in a multi-cloud environment.
Privacy in IoT
- Introduction to IoT Privacy
- Definition: Understanding the privacy implications of the Internet of Things (IoT) ecosystem.
- Example: Recognizing how IoT devices collect and process personal data in various contexts.
- IoT Governance
- Definition: Establishing policies and practices to govern the use of IoT devices while considering privacy implications.
- Example: Developing guidelines for secure and privacy-aware deployment of IoT devices within an organization.
- IoT Security & Privacy Issues
- Definition: Examining security and privacy challenges associated with IoT devices.
- Example: Identifying vulnerabilities in IoT devices that could lead to unauthorized access or data breaches.
- IoT Privacy Challenges
- Definition: Addressing specific challenges related to preserving privacy in the context of IoT.
- Example: Mitigating concerns about the potential misuse of personal data collected by smart home devices.
- IoT Privacy Solutions
- Definition: Implementing strategies and technologies to enhance privacy in the IoT landscape.
- Example: Utilizing end-to-end encryption for data transmitted between IoT devices to safeguard user privacy.
