What is Privacy Preserving?

Privacy preservation is important when working with sensitive data within an organization. It consists of strategies and methodologies designed to protect data from unauthorized access, use, or disclosure during data processing and analysis.

By adopting privacy preservation, organizations can conduct effective research and analysis and make data-driven decisions in an ethical manner without compromising the confidentiality of the data owner.

For example, if a hospital were analyzing patient data to find out the number of patients who died of a heart attack, privacy preservation would be helpful as they don’t need to see the PII data of people who died but rather focus on executing their analysis correctly.

Privacy preservation is becoming more relevant in 2024 as there are more cyber attacks happening, resulting in more data breaches that expose personally identifiable information (PII).

Adopting privacy preservation techniques

  • Ensures regulatory compliance with global privacy laws like GDPR and CCPA
  • Builds trust between entities and their users, customers, or subjects by upholding the principles of minimal data access, encryption, and ethical data use.

Legal Frameworks and Compliance

Legal frameworks and compliance are important for privacy preservation. Organizations must comply with legal frameworks and regulatory bodies like HIPAA or GDPR, as they list the best standards for handling, processing, and protecting personal data.

There are three significant regulatory frameworks for privacy protection that everyone should be aware of:

These regulations mandate a range of compliance measures, such as:

  • Obtaining explicit consent for data collection and processing.
  • Ensuring data is used only for the purposes for which it was collected.
  • Implementing privacy-preserving techniques to anonymize or pseudonymize personal information.
  • Providing individuals with the right to access, correct, or delete their data.

Choosing to follow one of these standards not only ensures compliance but also showcases your organization’s commitment to privacy, thus building trust with users and customers.

Data Peace Of Mind

PVML provides a secure foundation that allows you to push the boundaries.


Privacy-Preserving Techniques

After understanding the need for privacy preservation and the governing bodies that are available to govern data privacy, it’s important to understand the techniques to preserve privacy.

Some common techniques involve:

  • Data anonymization: This consists of modifying personal information so that individuals cannot be readily identified. This includes methods like pseudonymization, where identifiable information is replaced with artificial identifiers, and aggregation, where data is compiled into summary form to prevent individual identification.
  • Encryption techniques: Techniques like homomorphic encryption allow encrypted data computations, letting organizations make data-driven decisions without exposing the underlying data.
  • Differential privacy: Add noise to data or queries to ensure that the output of a database query gives out minimal information about any individual entry. This allows organizations to share aggregate information about a dataset while safeguarding individual data points.

Each technique aims to minimize privacy risks associated with data processing and analysis. Therefore, understand each technique well before selecting the technique for your use case.

Implementing Privacy Preserving Measures

If you’re implementing privacy preservation, you need to implement it at two levels right from the start: organizational operations and current systems.

This is done for three main reasons:

  • Compliance with legal requirements: Many jurisdictions have strict data protection regulations. Therefore, integrating privacy-preserving measures helps ensure compliance with these laws and avoids potential fines and legal issues.
  • Risk management: This lets you proactively address privacy concerns that ultimately reduce the risk of data breaches and privacy incidents.
  • Building trust with customers: When your data is stored securely, no one can really comprehend it. Therefore, even in the case of a data breach, your data is still incomprehensible, so your customer data is not at risk of being exposed.

It’s important to implement privacy right from the start. To do so, here are some high-level steps that your organization can adopt:

  • Adopt privacy by design: This principle suggests that privacy be placed at the center of everything from system design to deployment. This helps adopt proactive measures, thus ensuring that privacy is a crucial part of the development process.
  • Conduct privacy impact assessments (PIAs): PIAs are used to identify and mitigate potential privacy risks at the early stages of project development. They help organizations understand how personal information is collected, used, and managed, ensuring that projects comply with privacy regulations and principles.
  • Training and awareness: Educate staff about the importance of privacy and the specific measures adopted by the organization.
  • Implementing technical measures: Deploy encryption, access controls, and other privacy-preserving technologies to protect data at rest, in transit, and during processing.

Challenges of Privacy Preserving

Even if you build a privacy preservation system in your organization, there are still challenges. In fact, two of the biggest challenges an organization can face are:

  • Complexity: Privacy-preserving technologies, such as homomorphic encryption and differential privacy, are quite challenging and time-consuming to build. Not only that, but they’re extremely resource-intensive. This can introduce computational overhead, leading to scalability issues.
  • Costs: Deploying privacy preservation measures is expensive. You need to invest in the technology and train your staff to adapt to it. These costs can be particularly challenging for small and medium-sized enterprises (SMEs).


Privacy preservation is important in data management. It ensures that your data is kept private while still allowing it to be used ethically for analysis.

Through the implementation of various techniques and adherence to legal frameworks, organizations can mitigate risks, comply with regulations, and build trust with their customers while ensuring that their sensitive data is stored securely.