Homomorphic encryption: how to protect data during processing

In today’s digital landscape, protecting sensitive information is no longer sufficient only during storage or transfer. The real challenge arises when data needs to be processed outside of your control—such as in public cloud services, third-party platforms, or decentralized systems. This is where homomorphic encryption comes into play, a technology that allows operations to be performed on encrypted information without ever revealing the original content, while maintaining the integrity of the results.

Unlike traditional methods, where decrypting data is an unavoidable step before any processing (with associated risks of breach), homomorphic encryption completely transforms this paradigm. Your data remains encrypted at every stage of the computational process.

When Data Must Remain Protected During Processing

The core issue is known in cryptography as the “trusted third party.” When you entrust confidential information to a cloud computing provider or a business partner for analysis, you must fully trust that organization. But what happens if the provider is compromised? Or if a government authority demands access to your data?

Homomorphic encryption eliminates this fundamental risk. Sensitive information never needs to be decrypted by the processor, which operates on an encrypted version while maintaining absolute confidentiality. No one, not even the server managing the calculations, can ever access the data in plain text.

How Calculations on Encrypted Data Work

The magic of homomorphic encryption lies in its algebraic property: it allows mathematical operations to be performed directly on encrypted text. Imagine sending a secret number to someone who—without knowing what the number is—can multiply it, add a value, or run complex algorithms. When they return the encrypted result and you decrypt it, you find it matches exactly what you would have obtained by processing the original number in plain text.

This mechanism is based on lattice-based cryptography, a mathematical structure that makes the technology resistant even to future attacks with quantum computers. It thus offers a long-term security solution, not vulnerable to the threats that already concern cryptography experts today.

The Three Pillars That Make Homomorphic Encryption Unique

System Compatibility: Homomorphic encryption enables encrypted calculations across different infrastructures—including blockchain networks—where operations and verifications can occur directly on the network without exposing sensitive data. This allows decentralized protocols to process private information while maintaining process transparency.

Resistance to Quantum Computing: As quantum threats loom on the horizon, this technology provides a built-in shield with the right building blocks. Data protected by homomorphic encryption remains secure even as revolutionary computational powers emerge.

Public Verifiability Without Exposure: Anyone can verify that calculations were performed correctly without ever discovering the content of the processed data. This significantly enhances trust in decentralized and public systems, essential for blockchain networks and government services.

Concrete Benefits of Homomorphic Encryption

Zero Trust Security Model: Total trust in service providers is no longer necessary. Your data is inaccessible to them, regardless of how many additional protections they implement.

Simplified Regulatory Compliance: Organizations subject to strict data protection and confidentiality regulations find this technology an elegant solution. Data is never exposed during processing, greatly simplifying compliance.

Access to Advanced Tools Securely: Artificial intelligence, machine learning, and predictive analytics on encrypted datasets become finally feasible. Sectors that previously had to sacrifice privacy for insights can now do both.

Applications in Critical Sectors: From Finance to Healthcare

In the financial sector, banks and intermediaries perform fraud detection, credit risk modeling, and performance forecasting on encrypted data. Transactions and customer profiles remain protected during processing.

In healthcare, hospitals and research centers analyze medical records, clinical trial data, and patient information on cloud platforms without revealing identities or sensitive medical details. Research accelerates while privacy remains inviolable.

In retail and consumer services, companies analyze purchasing behaviors and search patterns in encrypted form, monetizing insights without compromising user privacy.

In the public sector, government agencies transmit citizen data securely, interact with other entities via blockchain networks, and maintain regulatory traceability in healthcare, tax, and identification systems.

Toward a Future with Integrated Privacy

Homomorphic encryption marks a turning point in the history of cybersecurity. As digitalization accelerates and regulatory requirements tighten, technologies like this will become increasingly critical. The future vision is a digital ecosystem where privacy is not an afterthought but a fundamental principle embedded in every aspect of online interaction. In this scenario, homomorphic encryption will be one of the pillars supporting data protection by default, ensuring information remains private even when processed in the most exposed contexts.