Popular GitHub Repositories for Gpg Encryption

A highly extensible Markdown editor. Version control, AI Copilot, mind map, documents encryption, code snippet running, integrated terminal, chart embedding, HTML applets, Reveal.js, plug-in, and macro replacement.

A unified framework for privacy-preserving data analysis and machine learning

IBM Fully Homomorphic Encryption Toolkit For Linux. This toolkit is a Linux based Docker container that demonstrates computing on encrypted data without decrypting it! The toolkit ships with two demos including a fully encrypted Machine Learning inference with a Neural Network and a Privacy-Preserving key-value search.

Concrete ML: Privacy Preserving ML framework using Fully Homomorphic Encryption (FHE), built on top of Concrete, with bindings to traditional ML frameworks.

A Privacy-Preserving Framework Based on TensorFlow

PYthon For Homomorphic Encryption Libraries, perform encrypted computations such as sum, mult, scalar product or matrix multiplication in Python, with NumPy compatibility. Uses SEAL/PALISADE as backends, implemented using Cython.

VULNRΞPO - Free vulnerability report generator and repository, end-to-end encrypted! Templates of issues, CWE,CVE,MITRE ATT&CK,PCI DSS, import Nmap/Nessus/Burp/OpenVAS/Bugcrowd/Trivy, Jira export, TXT/JSON/MARKDOWN/HTML/DOCX, attachments, automatic changelog, stats, vulnerability management, bugbounty, local ai/llm, super fast pentest reporting!

Security and Privacy Risk Simulator for Machine Learning (arXiv:2312.17667)

?️ A book and repo to get you started programming voice computing applications in Python (10 chapters and 200+ scripts).

CryptoNets is a demonstration of the use of Neural-Networks over data encrypted with Homomorphic Encryption. Homomorphic Encryptions allow performing operations such as addition and multiplication over data while it is encrypted. Therefore, it allows keeping data private while outsourcing computation (see here and here for more about Homomorphic E

Open-source CMS, Document Collaboration, Microblogging, and Publishing with AI Chatbot and AI Coding Agent supporting most Cloud AI providers

Neural Networks that invent their own encryption :key:

Lightweight, standalone, multi-platform, and privacy focused local LLM chat interface with optional encryption

zero-knowledge chat suite

Privacy -preserving Neural Networks

Homomorphic Encryption and Federated Learning based Privacy-Preserving

End-to-end encrypted, ephemeral, self-hosted terminal chat — no accounts, no history, no cloud.

Federated Learning with Differential Privacy and Homomorphic Encryption.

Federated learning with homomorphic encryption enables multiple parties to securely co-train artificial intelligence models in pathology and radiology, reaching state-of-the-art performance with privacy guarantees.

Efficient and Straggler-Resistant Homomorphic Encryption for Heterogeneous Federated Learning