What are privacy-enhancing technologies?
Protecting data in use
Standard means of data encryption provide a high level of protection for data at rest and in transit. However, when the data needs to be used, whether for human analysis or as part of an automated system, it must be decrypted. Decrypting data creates an opportunity for plaintext to be exposed to unauthorized parties, whether intentionally by malicious actors or unintentionally by honest but careless adversaries, within the system. To address this data layer threat, system architects are incorporating privacy-enhancing technologies (PETs) into their systems.
What are PETs?
PETs are technologies that aim to protect privacy and confidentiality of data in use without reducing necessary system functionality. Specifically, PETs are designed to do the following:
- Allow parties to collaborate while guaranteeing that any shared data will be used only for its intended purposes
- Glean insights from private data without revealing the sensitive contents of the data
- Carry out trusted computation in an untrusted environment
- Secure access to shared machine learning (ML) models without revealing sensitive data
- Add quantum-resistant data protections to the system
- Maintain complete control of the data throughout its lifecycle
In the full white paper, Leidos experts Liv d’Aliberti, Evan Gronberg, and Joe Kovba explain what technologies can protect privacy and confidentiality of data in use without reducing necessary system functionality.
