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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 ↗112 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.
- GitHub · Repository created · First archived
DerKezorm/nexpaper ↗
Paperless-ngx for the home, the simple version: a light filing cabinet for the papers of a household or a small firm on your own server. One container, OCR and search, vaults, upload from the phone, import from Paperless-ngx.
- Hacker News · Posted on Hacker News · First archived
How much privacy should you expect at church? ↗
Hacker News discussion.
- GitHub · Repository created · First archived
Shishir-ip/AppDNS ↗
Automatically switch Android's Private DNS (DNS-over-TLS) based on the app you open. No VPN, no tracking, open source.
- GitHub · Repository created · First archived
9mtm/Web-Respect ↗
Accessible reading preferences. Clear consent controls. Your brand, your services and your backend.
- GitHub · Repository created · First archived
SmailDot/FreeKeep-for-Steam ↗
Browser extension that auto-claims free Steam games (free-to-keep promotions) in the background. No password, no server, 100% local. Chrome & Edge, 12 languages.
- OpenAlex · Published · First archived
Reproducibility of social science research using aggregate statistics with noise infused for differential privacy ↗
Privacy-preserving analytics such as differential privacy are designed to allow the analysis of sensitive datasets while protecting individuals’ privacy. Their deployment, however, has been controversial. Critics maintain that statistical noise injected to preserve privacy can degrade the quality and feasibility of social science research. We select a benchmark of empirical findings from 93 published social science studies involving regression analyses over aggregate statistics. We evaluate whether their findings replicate on privacy noise-infused data. Under privacy budgets typical in industr…
- OpenAlex · Published · First archived
When Trust and Privacy Pull in Opposite Directions: Consumer Decision Making with Conversational AI ↗
Drawing on the Stimulus–Organism–Response (S-O-R) framework, this study examines how consumers’ perceptions of information quality, personalization, explainability, and responsiveness are associated with purchase intention through their relationships with perceived usefulness, algorithmic trust, and privacy concern, while considering AI literacy as a boundary condition. Data from 588 Chinese online shoppers who completed a standardized shopping task through direct interaction with a conversational AI shopping assistant were analyzed using structural equation modeling. The results show that all…
- OpenAlex · Published · First archived
LLMDPA: pre-execution privacy auditing of DP-SGD via evidence-constrained semantic analysis ↗
Abstract Privacy auditing has emerged as a critical component for safeguarding data privacy in machine learning models. Existing empirical auditing methods heavily rely on model runtime states or post-deployment interfaces, resulting in substantial time costs and limited source-level localization of leakage causes. In contrast, the theoretical guarantees of provable privacy mechanisms provide a basis for efficient privacy auditing with source-level traceability before model training. However, the validity of such auditing depends on the semantic consistency of the underlying implementation, wh…
- Hacker News · Posted on Hacker News · First archived
Privacy, Full Disk Access and AI Agents ↗
Hacker News discussion.
- Hacker News · Posted on Hacker News · First archived
Muse and Grok bot are a privacy nightmare,so I created a self-hosted alternative ↗
Hacker News discussion.
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 ↗
Related threads
Explore related regions
These navigation suggestions are part of the map’s editorial structure, rather than measured evidence of a connection.