// THREAT DETECTION AND DATA PRIVACY TERM
Privacy by Design
Privacy by Design is an approach to building systems and products where data protection is a core requirement from the very beginning, rather than an afterthought. It means embedding privacy features directly into the design and architecture of a project.
TECHNICAL DEFINITION
Privacy by Design (PbD) is a proactive engineering methodology that embeds data protection principles, such as data minimization and purpose limitation, into the entire lifecycle of systems, technologies, and business processes. Mandated by regulations like GDPR (as 'Data Protection by Design and by Default'), it ensures privacy is a default setting, preventing privacy issues before they occur through the use of privacy-enhancing technologies (PETs).
BACKGROUND
Computer security is a subdiscipline within the field of information security. It focuses on protecting computer software, systems, and networks from threats that can lead to unauthorized information disclosure, theft, or damage to hardware, software, or data, as well as to the disruption or misdirection of the services they provide.
READ MORE ON WIKIPEDIASYNONYMS & ALIASES
- PbD
- Data Protection by Design
- Embedded Privacy
- Design for Privacy
- Proactive Privacy
- Secure by Design
USAGE NOTE
This term is foundational in modern data protection regulations like GDPR and is used to demonstrate a proactive, rather than reactive, approach to compliance.
DEVELOPERS
Organizations developing technology related to Privacy by Design.
Provides a widely used privacy, security, and governance software platform that helps organizations operationalize Privacy by Design principles, automate Privacy Impact Assessments (PIAs), and manage user consent and data subject requests.
Develops consumer electronics and software with a strong focus on embedding privacy protections directly into product architecture, utilizing technologies like on-device processing, differential privacy, and App Tracking Transparency.
Offers a data intelligence platform that uses machine learning to automatically discover, classify, and catalog sensitive and personal data across an organization's entire data landscape, enabling the foundational steps of Privacy by Design.
Implements a 'Privacy by Design' and 'Privacy by Default' methodology across its product development lifecycle, offering tools within its Azure and Microsoft 365 ecosystems for data governance, classification, and privacy risk management.
A U.S. government agency that develops cybersecurity standards and guidelines, including the NIST Privacy Framework, which provides a structured model for organizations to manage privacy risk and implement Privacy by Design concepts.
Develops a data security and governance platform that provides centralized, fine-grained access control over data across multiple cloud services, enabling organizations to embed privacy and security rules directly into their data infrastructure.
Utilizes AI to power its Data Command Center, a platform for unified data controls across privacy, security, and governance. It automates tasks like data mapping and risk assessments essential for a Privacy by Design approach.
Develops and implements privacy-enhancing technologies (PETs) like differential privacy and federated learning. Its Privacy Sandbox initiative aims to create new web standards to enhance user privacy by phasing out third-party cookies.