Information Privacy

Fully Homomorphic Encryption (FHE) enables computations on encrypted data without decryption, preserving data confidentiality throughout processing. This capability is particularly valuable in machine learning applications where sensitive data, such as healthcare records or financial information, must remain private.​ Application Overview In a typical scenario, a data owner encrypts their dataset using FHE and sends it […]

FHE enables computations on encrypted data without decryption, preserving confidentiality throughout processing. However, its implementation is complex, involving multiple entities:​Zama – Open Source Cryptography+1Zama – Open Source Cryptography+1Zama – Open Source Cryptography The interplay among these participants introduces challenges such as trust assumptions, potential collusion, and the need for verifiable computation to ensure integrity without

Fully Homomorphic Encryption (FHE) has rapidly evolved from a theoretical concept to a practical cryptographic tool, enabling secure computation on encrypted data. In her presentation “Introduction to Practical FHE and the TFHE Scheme”, delivered on April 30, 2020, at the Simons Institute’s Lattices: From Theory to Practice workshop, cryptographer Ilaria Chillotti provides a detailed and

Fully Homomorphic Encryption (FHE) is a groundbreaking cryptographic innovation that enables computation on encrypted data without needing to decrypt it. This capability preserves privacy throughout the data lifecycle, especially in untrusted environments like cloud servers or collaborative computations. In this article, we explore the core ideas based on Zvika Brakerski’s influential survey, Fundamentals of Fully

Homomorphic encryption (HE) has evolved from a theoretical curiosity into a cornerstone of modern privacy-preserving computation. Its development spans over four decades, marked by major breakthroughs in cryptography that have gradually turned the idea of computing on encrypted data into a practical reality. This article outlines the key milestones in the history of homomorphic encryption,

Homomorphic encryption (HE) is a powerful and advanced form of encryption that allows computations to be performed directly on encrypted data without ever needing to decrypt it. This capability significantly enhances data privacy, particularly in scenarios like cloud computing and outsourced data processing. In this article, we explore the fundamentals of homomorphic encryption, how it

Homomorphic encryption is an advanced cryptographic technique that allows computation on encrypted data without requiring access to the plaintext. This powerful capability addresses a growing need for privacy-preserving data processing, especially as more sensitive information is stored and processed in cloud environments and by third-party service providers. What Is Homomorphic Encryption? At its core, homomorphic

Effective risk assessment is at the core of any information security and privacy program. While Data Protection Impact Assessments (DPIAs) are often discussed in legal and compliance settings—especially under the GDPR—broader and more structured risk assessment models are found in ISO/IEC 27001, the international standard for Information Security Management Systems (ISMS). This article revisits the