Privacy-Preserving Analytics for Smart Meter (AMI) Data: a Hybrid Approach to Comply with CPUC Privacy Regulations

Advanced Metering Infrastructure AMI data from smart electric and gas meters enables valuable insights for utilities and consumers, but also raises significant privacy concerns. In California, regulatory decisions CPUC D.11-07-056 and D.11-08-045 mandate strict privacy protections for customer...

Private LoRA Fine-Tuning of Open-Source LLMs with Homomorphic Encryption

Preserving data confidentiality during the fine-tuning of open-source Large Language Models LLMs is crucial for sensitive applications. This work introduces an interactive protocol adapting the Low-Rank Adaptation LoRA technique for private fine-tuning. Homomorphic Encryption HE protects the...

Privacy Challenges in Image Processing Applications

As image processing systems proliferate, privacy concerns intensify given the sensitive personal information contained in images. This paper examines privacy challenges in image processing and surveys emerging privacy-preserving techniques including differential privacy, secure multiparty...

Encrypted Federated Search Using Homomorphic Encryption

The sharing of information between agencies is effective in dealing with cross-jurisdictional criminal activities; however, such sharing is often restricted due to concerns about data privacy, ownership, and compliance. Towards this end, this work has introduced a privacy-preserving federated...

Privacy Preserving Machine Learning Model Personalization through Federated Personalized Learning

The widespread adoption of Artificial Intelligence AI has been driven by significant advances in intelligent system research. However, this progress has raised concerns about data privacy, leading to a growing awareness of the need for privacy-preserving AI. In response, there has been a seismic...

NCSC Guidance on “Advanced Cryptography”

The UK's National Cyber Security Centre just released its white paper on "Advanced Cryptography," which it defines as "cryptographic techniques for processing encrypted data, providing enhanced functionality over and above that provided by traditional cryptography." It includes things like...

CryptoUNets: Applying Convolutional Networks to Encrypted Data for Biomedical Image Segmentation

In this manuscript, we demonstrate the feasibility of a privacy-preserving U-Net deep learning inference framework, namely, homomorphic encryption-based U-Net inference. That is, U-Net inference can be performed solely using homomorphic encryption techniques. To our knowledge, this is the first...

Silenzio: Secure Non-Interactive Outsourced MLP Training

Outsourcing the ML training to cloud providers presents a compelling opportunity for resource constrained clients, while it simultaneously bears inherent privacy risks, especially for highly sensitive training data. We introduce Silenzio, the first fully non-interactive outsourcing scheme for the...

Lattica Emerges from Stealth to Solve AI’s Biggest Privacy Challenge with FHE

Lattica’s cloud-based solution uses Fully Homomorphic Encryption to query encrypted data on AI models without decrypting it, preserving privacy and bolstering security...

EFFACT: a Highly Efficient Full-Stack FHE Acceleration Platform

Fully Homomorphic Encryption FHE is a set of powerful cryptographic schemes that allows computation to be performed directly on encrypted data with an unlimited depth. Despite FHE's promising in privacy-preserving computing, yet in most FHE schemes, ciphertext generally blows up thousands of time...

FLSSM: a Federated Learning Storage Security Model with Homomorphic Encryption

Federated learning based on homomorphic encryption has received widespread attention due to its high security and enhanced protection of user data privacy. However, the characteristics of encrypted computation lead to three challenging problems: "computation-efficiency", "attack-tracing" and...

Measuring Computational Universality of Fully Homomorphic Encryption

Many real-world applications, such as machine learning and graph analytics, involve combinations of linear and non-linear operations. As these applications increasingly handle sensitive data, there is a significant demand for privacy-preserving computation techniques capable of efficiently...

Apple Unveils Homomorphic Encryption Package for Secure Cloud Computing

Apples open-source "swift-homomorphic-encryption" package revolutionizes privacy in cloud computing. It allows computations on encrypted data without decryption, safeguarding…...

How FHE Technology Is Making End-to-End Encryption a Reality

By Uzair Amir Is End-to-End Encryption E2EE a Myth? Traditional encryption has vulnerabilities. Fully Homomorphic Encryption FHE offers a new hope… This is a post from HackRead.com Read the original post: How FHE Technology Is Making End-to-End Encryption a Reality...

Zama Secures $73M Series A Lead for Homomorphic Encryption

By cyberwire Company Open Sources FHE Libraries to Build Privacy-Preserving Blockchain and AI Applications for the First Time. This is a post from HackRead.com Read the original post: Zama Secures $73M Series A Lead for Homomorphic Encryption...

FrodoPIR: New Privacy-Focused Database Querying System

The developers behind the Brave open-source web browser have revealed a new privacy-preserving data querying and retrieval system called FrodoPIR. The idea, the company said, is to use the technology to build out a wide range of use cases such as safe browsing, scanning passwords against breached...

Researchers Demonstrate New Side-Channel Attack on Homomorphic Encryption

A group of academics from the North Carolina State University and Dokuz Eylul University have demonstrated what they say is the "first side-channel attack" on homomorphic encryption that could be exploited to leak data as the encryption process is underway. "Basically, by monitoring power...

Fully-Homomorphic-Encryption - Libraries And Tools To Perform Fully Homomorphic Encryption Operations On An Encrypted Data Set

This repository contains open-source libraries and tools to perform fully homomorphic encryption FHE operations on an encrypted data set. About Fully Homomorphic Encryption Fully Homomorphic Encryption FHE is an emerging data processing paradigm that allows developers to perform transformations o...

Indistinguishability Obfuscation

Quanta magazine recently published a breathless article on indistinguishability obfuscation -- calling it the "crown jewel of cryptography" -- and saying that it had finally been achieved, based on a recently published paper. I want to add some caveats to the discussion. Basically, obfuscation...

Google Releases Basic Homomorphic Encryption Tool

Google has released an open-source cryptographic tool: Private Join and Compute. From a Wired article: Private Join and Compute uses a 1970s methodology known as "commutative encryption" to allow data in the data sets to be encrypted with multiple keys, without it mattering which order the keys a...