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What are privacy protection technologies (PET)?

Modern businesses will need to work with customer data in one way or another. The COVID-19 pandemic has proven that the only companies that will survive in the future are those that are ready to embrace technology. While technologies such as the Internet of Things and artificial intelligence have undeniable advantages, they have also presented complications.

Managing the data of your customers or visitors to your site is a bit like having intimate access to their home. If companies don’t prioritize privacy and data security in the early stages of building their business, it can come back to haunt them at the most inconvenient times. Hence the growing importance of privacy protection technologies (PET).

This guide will explore what privacy technologies are and how your business can benefit from using them.

What are privacy technologies?

Privacy Enhancing Technologies or PET are designed to prevent data leaks while balancing privacy and usability. Some PETs even prevent malicious actors from identifying who owns the collected data – if a leak were to occur, the data would be virtually useless to cybercriminals.

Other PETs prevent costly data breaches through cryptographic protection when processing data. PET can also take the form of remote audit services that monitor and ensure that data is only processed for the right purposes. This minimizes the risk of data leaks and breaches.

Your business may have all the data it needs and know all there is to know about it, but building online and software-based services that are private by design is a challenge. PET can help you launch privacy-friendly services that prevent disastrous data leaks.

Types of privacy-enhancing technologies

In truth, the term “privacy technology” is a bit vague. It refers to any technology that represents the fundamental elements of data protection. As such, any tool that minimizes the use of personal data while maximizing data security can fall under this umbrella. Types of PET include:

Data masking

Traffic analysis is one of the biggest threats to data security and privacy. Malicious actors should not be able to monitor your footprint or online communications. You can prevent this incursion by using a reputable VPN provider to encrypt your communications when connected to a public network. It’s one of the simplest, yet most effective strategies you can use to keep your online footprint hidden. A good VPN will conceal your browsing history, personal data, login details, and IP address, making it much harder for you to be tracked online.

Pseudonymization and obfuscation are other forms of data masking. This is where sensitive data is distorted, obscured or replaced with fake data. Companies can go so far as to use machine learning algorithms to create synthetic data.

Businesses can also protect their customers by minimizing the amount of personal data they collect. This is called data minimization.


Cryptographic tools are the oldest forms of PET. For example, we have seen how effective single-field derivative encryption can be for securing crypto assets through crypto wallets.

Homomorphic encryption is a good example of modern cryptographic methods used in data privacy. The process involves encoding the data so that operations on the data can still be performed without decryption. It’s similar to how you can open a zip folder and make changes to the files inside.

There are two main types (some sources cite three) of homomorphic encryption:

  • Full homomorphic encryption (FHE)
  • Partial homomorphic encryption (PHE)

Secure Multiparty Computing (SMPC) is another form of cryptography used in PET. In this method, parts of a block of data are encrypted by multiple parties, similar to how P2P swarm systems work.

Differential privacy in data cryptography is functionally similar to obfuscation. The data is masked by a layer of statistical noise. This method is often used in statistics because it can hide data about individuals while revealing data that allows you to identify patterns related to a group.

Finally, zero-knowledge proof (ZKP) works similarly to homomorphic encryption, where data can be used without revealing it. ZKP allows you to validate data (or use it for validation) without decryption.

How to choose a PET?

There are many awesome privacy enhancement tools in the market. However, it is important to identify how they would fit into your software stack and IT infrastructure. Therefore, you should recognize the specific data privacy needs of your departments and your business. You should:

  • Identify the volume and type of data your business manages. Is the majority structured or unstructured?
  • Identify the third-party services with which your data is shared (if applicable). If your data is passed on to third parties, homomorphic encryption is your best option.
  • Distinguish the parts of the data you need. For example, do you need full access to the dataset or only the result/output? Can you deny sensitive data that can be used to identify individuals (personally identifiable information)?
  • Identify what the data will be used for. Will it be used for statistics, market data, or machine learning model training, and other similar uses?
  • Assess your IT infrastructure and your network and compute capabilities. This will help you determine if a particular PET is compatible with your company’s resources. Additionally, you can use this information to determine which parts of your IT infrastructure need upgrading.
  • Build the necessary provisions into your budget, as PETs can be expensive – some more than others.


There are many different types of PET, each designed to solve a specific business problem. While some are better for aggregate analyses, others are more suited for precise results. Likewise, some may be ideal for extracting insights from sensitive data, while others are better for data mining.

Organizations from different sectors are collecting and analyzing data from all modalities at an unprecedented rate. Thus, they need to ensure that they are collecting data securely while analyzing it in a demonstrable way. It is essential for the public image and the financial future of your company. PETs should be a small part of a larger zero-trust solution. It is important to avoid being myopic when considering cybersecurity and data privacy.

About the Author: Gary Stevens is an IT specialist who is a part-time Ethereum developer working on open source projects for QTUM and Loopring. He is also a part-time blogger on Privacy Australiawhere he discusses online security and privacy.

Editor’s note: The opinions expressed in this guest author article are solely those of the contributor and do not necessarily reflect those of Tripwire, Inc.