Search Results for "privacy"
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Showing 185 open source projects for "privacy"
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OpenAI Privacy Filter
Bidirectional token-classification model for identifiable info
OpenAI Privacy Filter is an open-weight machine learning model designed to detect and mask personally identifiable information in text with high efficiency and contextual awareness. It operates as a bidirectional token classification system that labels sensitive data in a single forward pass rather than generating text sequentially, enabling fast processing for large datasets. -
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Mercury Browser
Privacy-focused web browser fork of Firefox
...It also includes usability patches that bring back features like the classic top bar and supports unsigned extensions for added flexibility. Mercury is tailored for users prioritizing speed and privacy and is available for both Linux and Windows. -
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DuckDuckGo Android App
Privacy browser for Android
DuckDuckGo is an app that gives you utmost privacy when browsing online. It stops you from getting tracked and protects your personal and private information, no matter where the internet may take you. Apart from providing standard browsing functionality, DuckDuckGo blocks all hidden third-party trackers, forces sites to use an encrypted connection where available, and provides a Privacy Grade rating for each website you visit. -
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Ungoogled Chromium Windows
Windows packaging for ungoogled-chromium
...Users who need a modern browser engine with wide compatibility but without Google branding or background services can leverage this repository to produce Windows installers or portable builds that respect local privacy preferences. -
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Opacus
Training PyTorch models with differential privacy
...Open source, modular API for differential privacy research. Everyone is welcome to contribute. ML practitioners will find this to be a gentle introduction to training a model with differential privacy as it requires minimal code changes. Differential Privacy researchers will find this easy to experiment and tinker with, allowing them to focus on what matters. -
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SearXNG
Free internet metasearch engine which aggregates
SearXNG is a free and open-source metasearch engine designed to aggregate results from multiple search engines while prioritizing user privacy and anonymity. Instead of maintaining its own index, it queries numerous external search providers and merges the results into a single interface, increasing coverage and diversity of information. One of its core principles is privacy, as it does not track users, store personal data, or create search profiles, making it a strong alternative to traditional search engines. . ... -
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Helium Browser
Private, fast, and honest web browser
Helium is a Chromium-based web browser designed to deliver privacy, speed, and simplicity by removing Google’s proprietary services, telemetry, and bloat. It’s built atop ungoogled-chromium, extending its philosophy with additional privacy features, design refinements, and user experience improvements aimed at transparency and control. Helium blocks ads and trackers by default through an integrated, unbiased uBlock Origin extension prepackaged as a native browser component. ... -
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Tribler
Privacy enhanced BitTorrent client with P2P content discovery
Tribler is a decentralized, privacy-enhanced BitTorrent client developed by researchers at Delft University of Technology. It introduces built-in anonymity using a Tor-like onion routing network and integrates its own blockchain for economic incentives and trust management. Tribler supports standard torrenting features along with distributed search, self-contained channels, and peer reputation. -
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Synthetic Data Generator
SDG is a specialized framework
Synthetic Data Generator is an open-source framework designed to generate high-quality synthetic tabular datasets that replicate the statistical characteristics of real data while avoiding privacy risks. The platform enables developers and data scientists to create artificial datasets that preserve important relationships between variables without containing sensitive personal information. This makes the generated data suitable for tasks such as machine learning model training, testing software systems, sharing datasets across organizations, and conducting research without violating privacy regulations. ... -
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Appfl
Advanced Privacy-Preserving Federated Learning framework
APPFL (Advanced Privacy-Preserving Federated Learning) is a Python framework enabling researchers to easily build and benchmark privacy-aware federated learning solutions. It supports flexible algorithm development, differential privacy, secure communications, and runs efficiently on HPC and multi-GPU setups. -
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Proton VPN GTK App
Official ProtonVPN Linux app
...It supports features expected of a full VPN client—such as secure tunnels, automatic reconnection, and location selection—while respecting desktop conventions like system tray icons and notifications. The GTK client helps bring ProtonVPN’s privacy-focused service to the Linux ecosystem in a way that fits naturally with widely used Linux DEs, making secure connectivity accessible to users who prefer open systems for development, business, or privacy reasons. -
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Sideband
LXMF client for Android, Linux and macOS to communicate with people
Sideband is a privacy-focused, peer-to-peer mesh messaging protocol and platform that allows users to communicate directly over local networks or the internet without servers. It emphasizes metadata resistance and secure message delivery, working effectively in offline, low-bandwidth, or disaster recovery scenarios. Built-in Rust, Sideband supports encrypted group messaging, file transfers, and network self-discovery. -
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Pfl Research
Simulation framework for accelerating research
A fast, modular Python framework released by Apple for privacy-preserving federated learning (PFL) simulation. Integrates with TensorFlow, PyTorch, and classical ML, and offers high-speed distributed simulation (7–72× faster than alternatives). -
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RoboSats
A simple and private bitcoin exchange
...Designed with a strong focus on usability and anonymity, it's especially popular among privacy advocates and Bitcoin maximalists. -
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Operit AI
Powerful Android AI agent with tools, automation, and Linux shell
...A standout aspect of the project is its built-in Ubuntu 24 environment, which enables users to run Linux commands, scripts, and development tools in a mobile context. Operit supports both local and remote AI models, including offline execution through frameworks like llama.cpp and MNN, helping preserve user privacy while maintaining flexibility. Operit also includes an intelligent memory system that stores, organizes, and retrieves user interactions to provide more personalized and context-aware responses. In addition, it offers workflow automation, plugin extensibility, & a rich tool ecosystem, making it suitable for advanced productivity. -
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ValueCell
Community-driven, multi-agent platform for financial applications
...ValueCell supports integrations with multiple language model providers and market data sources, giving developers flexibility in customizing agents and incorporating external APIs to enhance insights. Sensitive user data is stored locally, a design choice that prioritizes privacy and security while still enabling rich analytic workflows. -
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AgenticSeek
Fully Local Manus AI. No APIs, No $200 monthly bills
...It also supports hands-free workflows such as automated web form interaction and information extraction. Overall, the project functions as a self-hosted, multi-capability AI agent designed for users who prioritize autonomy, privacy, and local execution. -
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nesa
Run AI models end-to-end encrypted
nesa is an open-source initiative focused on building decentralized AI infrastructure that enables secure, verifiable, and privacy-preserving machine learning and inference across distributed environments. The project aims to address key challenges in modern AI systems, such as data privacy, trust, and centralization, by leveraging cryptographic techniques and decentralized architectures. NESA allows developers to run AI computations in a way that ensures data integrity and confidentiality, making it particularly relevant for applications involving sensitive or regulated data. ... -
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Home Assistant
Open source home automation that puts local control and privacy first
Home Assistant is a powerful open source home automation app that prioritizes local control and privacy. It offers great security and features while keeping your data securely out of the cloud. It can give you control of all your devices from a single, mobile-friendly interface and will track the state of all these devices so you don’t have to. Home Assistant is powered by a worldwide community and runs ideally on a Raspberry Pi or a local server. -
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Open Notebook
An Open Source implementation of Notebook LM with more flexibility
Open Notebook is an open-source, privacy-focused alternative to Google’s Notebook LM that gives users full control over their research and AI workflows. Designed to be self-hosted, it ensures complete data sovereignty by keeping your content local or within your own infrastructure. The platform supports 16+ AI providers—including OpenAI, Anthropic, Ollama, Google, and LM Studio—allowing flexible model choice and cost optimization. -
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RuView
Turn WiFi signals into real-time human sensing and spatial awareness.
...Built on the concept of WiFi DensePose, it analyzes disturbances in WiFi Channel State Information (CSI) caused by human movement to reconstruct body position, breathing patterns, heart rate, and presence. Unlike traditional vision systems, RuView operates without cameras, wearables, or cloud connectivity, making it a privacy-first sensing solution. The system runs on low-cost hardware such as ESP32 sensor meshes and performs signal processing and machine learning directly at the edge. By learning the RF signature of each environment over time, RuView adapts automatically to different spaces and improves its sensing accuracy. Designed for applications ranging from healthcare monitoring to disaster response, it enables spaces to gain spatial awareness using the radio signals already present in the environment. -
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NVIDIA FLARE
NVIDIA Federated Learning Application Runtime Environment
NVIDIA Federated Learning Application Runtime Environment NVIDIA FLARE is a domain-agnostic, open-source, extensible SDK that allows researchers and data scientists to adapt existing ML/DL workflows(PyTorch, TensorFlow, Scikit-learn, XGBoost etc.) to a federated paradigm. It enables platform developers to build a secure, privacy-preserving offering for a distributed multi-party collaboration. NVIDIA FLARE is built on a componentized architecture that allows you to take federated learning workloads from research and simulation to real-world production deployment. -
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ROMM
A beautiful, powerful, self-hosted rom manager and player
...Romm also supports widgets, customization options, and theme choices so users can tailor the visual experience to their preferences while maintaining performance and responsiveness. Privacy is a highlight, with local indexing and search functions that operate without sending data to external servers unless explicitly permitted. -
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Gretel Synthetics
Synthetic data generators for structured and unstructured text
...Generate unlimited data in minutes with synthetic data delivered as-a-service. Synthesize data that are as good or better than your original dataset, and maintain relationships and statistical insights. Customize privacy settings so that data is always safe while remaining useful for downstream workflows. Ensure data accuracy and privacy confidently with expert-grade reports. Need to synthesize one or multiple data types? We have you covered. Even take advantage or multimodal data generation. Synthesize and transform multiple tables or entire relational databases. ... -
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Nitter
Alternative Twitter front-end
Nitter is an open-source alternative frontend for Twitter designed to provide a privacy-focused and lightweight way to browse content without interacting directly with the official platform. It acts as a proxy between the user and Twitter, ensuring that requests are handled by the backend server rather than exposing the user’s IP address or browser fingerprint. The interface is intentionally minimalistic and removes elements such as advertisements, tracking scripts, and algorithmic timelines, presenting content in a chronological and distraction-free format. ...