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Earlier sources: Privacy
This security thread follows privacy through original research, public projects, and source reports. Read the evidence below to see which developments are represented in SYMTRI’s archive.
SYMTRI organizes observations from public sources into a living map. Connections reflect shared subject matter; they do not establish causation or endorse a source.
Open in the map ↗115 classified signals in the fourteen-day window. These counts include signals awaiting readable evidence.
Earlier sources
Up to ten sources with readable evidence, ordered by their feed timestamp. These archive sources can be older than the live fourteen-day window. This list is a sample, not a measure of total activity. Dates distinguish paper publication, repository creation, model/dataset activity, Hacker News posts, and KEV catalog additions. “First archived” records when SYMTRI first stored the signal.
- Hacker News · Posted on Hacker News · First archived
The Open Anonymity Project – frontier AI models with privacy ↗
Hacker News discussion.
- arXiv · Published · First archived
Quantum Advantage for Two-Party Differential Privacy ↗
We introduce information-theoretically private quantum protocols for two-party Hamming distance when both parties must output the same estimate. Classically, for input length $n$, information-theoretic protocols require $Ω(\sqrt{n})$ error under pure differential privacy and $Ω(\sqrt{n}/\log n)$ error under strong approximate differential privacy, whereas computational security permits $O(1)$ error. In Klauck's honest, nonpreemptive, message-preserving model, we give an $O(n)$-communication quantum protocol with pure $\varepsilon$ quantum differential privacy (QDP) and expected error at most $…
- GitHub · Repository created · First archived
shitianyaa/FriendlySchool ↗
FriendlySchool — LSPosed module for ad removal and privacy protection in YiCampus, WakeUp and JMComic3
- GitHub · Repository created · First archived
idkrandombuilds/SINdle ↗
A hidden, password protected library for your most secret Kindle books. KoReader Patch.
- GitHub · Repository created · First archived
ali-rajabpour/ZoDAV ↗
Private, self-hosted Zotero WebDAV file sync over Tailscale or Headscale, plus zodav-audit: conformance, integrity and repair checks for any Zotero WebDAV server.
- GitHub · Repository created · First archived
SysAdminDoc/HushTelegram ↗
HushTelegram v0.0.9: Morphe patches that take sponsored messages, search ads, Stories and upsells out of Telegram and keep its usage reports on your phone. 25 patches for Telegram 12.10.6.
- OpenAlex · Published · First archived
Fine-Grained Privacy Leakage Detection in OpenHarmony Apps ↗
In recent years, the distributed operating system OpenHarmony has gained significant popularity. As the number of OpenHarmony apps grows rapidly, privacy abuse and data leakage have emerged as critical concerns. However, the untyped and highly flexible nature of Ark bytecode poses substantial challenges. We propose HScope, a novel fine-grained program analysis framework designed to directly analyze OpenHarmony app bytecode and identify privacy risks. HScope employs abstract interpretation to model the dynamic behaviors of OpenHarmony apps, enabling precise resolution of indirect calls and the…
- OpenAlex · Published · First archived
How Safe Is Your Screen? Understanding and Detecting Privacy Leaks in Sensitive Activities ↗
Android apps handle sensitive data, often displayed on screens (i.e., Activities), and protecting these activities is vital for ensuring user privacy. Several studies have demonstrated the risk of private data leakage via screen capture and identified malware exploiting this vulnerability. To mitigate such threats, Google introduced FLAG_SECURE, an activity-level security feature that protects an Activity when set by blocking screen capture and restricting display on non-secure devices. Proper usage of this security feature could significantly reduce data leakage risks. However, to the best of…
- OpenAlex · Published · First archived
When Optimizations Backfire: The Paradox of Plaintext Optimizations in Privacy-Preserving ML Compilers ↗
Growing concerns about data security and privacy have fueled the widespread adoption of Privacy-Preserving Machine Learning (PPML). Cryptography-based PPML, which allows computation directly on encrypted data, significantly mitigates data leakage risks. To facilitate its adoption, Ciphertext Machine Learning Compilers (CMLCs) automate the translation of high-level ML procedures into low-level circuits for encrypted data. Recently, CMLCs have increasingly adopted infrastructure from Plaintext Machine Learning Compilers (PMLCs). While integrating Plaintext-Domain Optimization Passes (PDOPs) into…
- Hacker News · Posted on Hacker News · First archived
Show HN: Paperweight – local-first, open-source email cleanup and privacy tool ↗
Hi HN, After building for 7 months, I'm excited to announce Paperweight V1. The idea is that your inbox knows who you ever interacted with and knows where your data lives. Every account you ever created, every service you signed up for, and every online purchase is connected to your email. Most people have hundreds of accounts they've forgotten about, creating security risks and privacy exposure. Paperweight scans your email history locally to fi…
Live window recorded . This is the ingestion observation time, not the publication or discovery date of each source.
How to assess evidence about Privacy
Check each original source for its methods, release status, limitations, and supporting data. A repository announcement, a preprint, and a published study provide different kinds of evidence. SYMTRI’s subject classification helps discovery; it does not independently validate the source’s claims.
See the collection and counting methodology ↗ · Read the weekly synthesis ↗
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These navigation suggestions are part of the map’s editorial structure, rather than measured evidence of a connection.