// THREAT DETECTION AND DATA PRIVACY TERM

Privacy Engineering

Privacy engineering is the practice of embedding privacy protections directly into the design and operation of information systems, products, and services, rather than treating privacy as an afterthought.

TECHNICAL DEFINITION

Privacy Engineering is the technical discipline of integrating privacy-by-design principles into system architectures, software development lifecycles, and data processing operations, leveraging technical controls and privacy-enhancing technologies (PETs) to enforce data protection regulations (e.g., GDPR, CCPA) and organizational privacy policies.

BACKGROUND

In the context of information security, social engineering is the use of psychological pressure to influence people to perform actions or divulge confidential information. It has also been more broadly defined as "any act that influences a person to take an action that may or may not be in their best interests." A type of confidence trick for the purpose of information gathering, fraud, or system access, it differs from a traditional "con" in the sense that it is often one of many steps in a more complex fraud scheme. Phishing is a type of social engineering. Researchers have developed detection techniques and cybersecurity educational programs.

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SYNONYMS & ALIASES

  • Privacy-by-Design
  • Data Privacy Engineering
  • Privacy Enhancing Technologies (PETs) Implementation
  • Secure Privacy Design

USAGE NOTE

It is crucial for organizations to proactively build trust and ensure compliance with global data protection regulations.

DEVELOPERS

Organizations developing technology related to Privacy Engineering.

  • Google

    Develops and deploys privacy-preserving technologies such as differential privacy, federated learning, and secure multi-party computation across its products and services, driving the practical application of privacy engineering.

  • Microsoft

    Conducts extensive research and development in privacy-enhancing technologies (PETs) including homomorphic encryption (e.g., SEAL library), differential privacy, and confidential computing, integrating privacy-by-design principles into its cloud and enterprise solutions.

  • Apple

    Known for its strong commitment to privacy-by-design, developing technologies for on-device data processing, differential privacy for analytics, and advanced encryption to protect user data across its hardware and software platforms.

  • National Institute of Standards and Technology (NIST)

    A U.S. government agency that develops and publishes standards, frameworks (like the NIST Privacy Framework), and best practices for cybersecurity and privacy engineering, providing foundational guidance for technology developers in both public and private sectors.

  • Privitar

    Provides enterprise software solutions for data privacy, enabling organizations to use sensitive data safely. Its technology focuses on advanced data anonymization, pseudonymization, and policy enforcement, applying core privacy engineering principles.

  • Thales

    A global technology leader in aerospace, defense, and security, Thales develops advanced cybersecurity solutions including data protection, encryption, identity and access management, and secure communication systems, incorporating robust privacy engineering into critical infrastructure.

  • Defense Advanced Research Projects Agency (DARPA)

    Funds and directs cutting-edge research and development in advanced technologies for U.S. national security, including significant projects in secure multi-party computation, homomorphic encryption, and other privacy-enhancing technologies crucial for future defense capabilities and privacy engineering.

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