Alan Westin’s theory describes privacy as the control over how information about a person is handled and communicated to others. Irwin Altman added that privacy includes limiting social interaction and included regulating personal space and territory.

Personal data includes any information that by itself or in conjunction with other elements can be used to identify an individual, such as their name, age, gender, personal identification number, race, religion, address, email address, biometric data, device IDs, medical data, and genetics data, based on the regulations defined in the country where the orginated from.

Privacy refers to an individual’s ability to keep their information, whether it is personal or non-personal data, to themselves and share data based on their consent. Privacy helps individuals maintain autonomy over their personal lives.

Data privacy focuses on the use and governance of personal data and policies...

The concept of PbD was created by Ann Cavoukian in the 1990s and presented in her 2009 presentation, “Privacy by Design: The Definitive Workshop.” As Cavoukian states, the concept of PbD encompasses more than just technology.

PbD is a framework that promotes the integration of privacy and data protection principles into the design and development of systems, products, and services.

The PbD framework has seven foundational principles. The objective of these principles is to ensure that privacy is embedded in every stage of a system’s development and that data subjects’ privacy rights are protected:

• Proactive not reactive measures: PbD requires that privacy considerations be integrated into the design and development of a system from the outset, rather than being added as an afterthought.
• Privacy as the default setting: PbD requires that privacy settings be set to the highest level by default and that users...

What is a privacy breach?

A privacy breach, also known as a data breach, refers to an incident where unauthorized individuals or entities gain access to confidential or sensitive information without proper authorization. This breach of privacy can occur in various forms, such as hacking, theft, accidental exposure, or improper handling of data. It typically involves the unauthorized access, acquisition, disclosure, or use of personal information, which may include personally identifiable information (PII) such as names, addresses, social security numbers, financial details, and login credentials.

Privacy breaches can have serious consequences for individuals, organizations, and even society. They can lead to identity theft, financial fraud, reputational damage, loss of trust, legal implications, and emotional distress for those affected. Protecting personal data and maintaining privacy is essential to ensure the security and well-being of individuals and maintain...

In an increasingly digital world, privacy has become a paramount concern for individuals, organizations, and societies at large. With the widespread collection and processing of personal data, it is essential to assess and mitigate privacy threats effectively.

Privacy threat modeling – definition

Privacy threat modeling is a proactive process that aims to identify and understand potential threats to privacy before they materialize. By examining the system’s architecture, data flows, and interactions, privacy threat modeling allows for the identification of vulnerabilities and risks that may compromise individuals’ privacy. It helps organizations anticipate and address privacy concerns during the design and development stages, ensuring privacy protections are integrated into the system from the outset.

The importance of privacy threat modeling

Privacy threat modeling offers several key benefits, including the following:

...

LINDDUN is a privacy threat modeling methodology that supports analysts in systematically eliciting and mitigating privacy threats in software architectures. This framework was developed by privacy experts at KU Leuven.

The LINDDUN framework consists of three main steps:

1. Model the system.
2. Elicit threats.
3. Mitigate threats.

Figure 1.2 – LINDDUN framework steps

Step 1 – modeling the system

In this step, it is crucial to gain a comprehensive understanding of the system or product being developed, including detailed knowledge of data flows. This entails comprehending how data is collected, processed, utilized, retained, and shared, as well as identifying the system’s users and their access methods. Additionally, it is essential to understand how the system interacts with other systems. To facilitate the analysis of privacy threats, LINDDUN employs DFDs as a means of capturing system or product...

Privacy-preserving ML has emerged as a response to the growing concerns about data privacy in AI and ML and the need to protect sensitive information while leveraging the power of ML algorithms. You will learn about ML and privacy-preserving ML techniques in the next chapter.

The following are some of the reasons why privacy-preserving ML is necessary:

• Protection of sensitive data: Privacy-preserving ML techniques enable organizations to utilize sensitive data without exposing it to potential breaches or unauthorized access. By implementing privacy safeguards, organizations can protect sensitive information such as PII, medical records, financial data, or proprietary business data. You will learn more in Chapters 5 to 8 on how to protect sensitive data using different privacy-preserving technologies.
• Compliance with privacy regulations: Many jurisdictions have enacted strict privacy regulations and data protection laws, such as the...

To summarize, we have acquired a high-level understanding of privacy, data privacy, PbD concepts, and privacy threat modeling. Furthermore, we have explored the importance of privacy-preserved ML through a case study.

Moving forward, the next chapter will provide a brief overview of different types of ML (supervised and unsupervised) and the phases involved in ML (data extraction, data preparation, model development, model deployment, and inferencing). Additionally, we will examine the privacy threats and attacks associated with each phase.