Methodology & Measurement Framework
dcoy

Privacy you can measure. The anti-surveillance platform.

Profile Blur Score: Methodology and Measurement.

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Whitepaper · Version 3.2 · May 2026 · dcoy.io

This document presents the Profile Blur Score methodology, platform architecture, and claim verification paths for dcoy. Every claim is backed by an external validator (EFF Cover Your Tracks, Optery) or an internal artifact (database log, dashboard event). Readers are encouraged to verify all claims using the free public tools cited throughout.

Note on this revision: Version 3.2 updates the v3.1 document to reflect current product state as of May 2026. Inline annotations distinguish target architecture from current implementation throughout. Claims that could not be backed have been softened or removed.

01 · Mission and position

Running the same logic, in reverse.

Surveillance companies aggregate every signal they can find about a person and convert that raw data into actionable intelligence profiles. Their clients are corporations, governments, political campaigns, and advertisers. The people being profiled have no visibility and no recourse.

dcoy is built in direct opposition to that infrastructure, running the same logic in reverse, on behalf of the individual.

Surveillance industrydcoy
ApproachAggregate signals, build profile, targetCorrupt signals, degrade profile, protect
EffectMakes individuals legible to institutionsMakes individuals illegible to institutions
ClientCorporations, governments, campaignsYou
Scale effectIntelligence improves with more dataProtection improves with more subscribers
AccountabilityNo visibility, no recourseMonthly score proves what is working
02 · Executive summary

Cross-platform, measurable, four layers live.

dcoy is a cross-platform consumer privacy platform that actively degrades commercial surveillance profiles across every device a subscriber uses. Unlike tools that attempt to block or hide activity, dcoy corrupts the data surveillance systems already have, making it statistically unreliable for targeting, pricing, and political manipulation.

The Profile Blur Score (PBS) is the mechanism by which dcoy proves this is working. It is a 0 to 100 index built from six components. Four components are live and contributing to the headline score today: broker removal, tracker SDK blocking, browser fingerprint noise injection (5.1 of 6 points verified against EFF Cover Your Tracks; canvas hash sub-surface under investigation), and behavioral noise injection. Location signal rotation is in design with zero PBS contribution pending implementation. Mobile advertising ID rotation is out of scope pending a user-guided flow design.

Every claim in this document is backed by an external validator or an internal artifact. The PBS Phase 1 ceiling of 78 reflects the exclusion of mobile advertising ID, social media on-platform data, and transaction history, all disclosed in every dashboard view.
03 · What dcoy claims and doesn't

The most important table in this document.

The following table summarises the status of each protection vector. Every "Live" status is backed by either an external validator (EFF, Optery) or a Tony-run dashboard log artifact.

StatusVectorPBS contribution
LiveData broker removal (28% of profile)Automated submissions to a regularly updated list of consumer-facing data brokers, with profile repopulation monitoring. Verifiable via Optery and Privacy Rights Clearinghouse.
LiveTracker SDK blocking (18%)An extensive blocklist of tracker SDK domains. Block log visible in real time in dashboard.
LiveBrowser fingerprint noise injection (6%)Page-level interception running in production on Chrome. Three sub-surfaces verified against EFF Cover Your Tracks weighting (WebGL renderer and hash, navigator JS surfaces, AudioContext). 5.1 of 6 points proven. Canvas hash sub-surface (0.9 pts) under investigation.
LiveBehavioral noise injection (12%)Score computation live in production since April 2026. Formula measures signals delivered against weekly target rate. Interest-graph coherence delta is the target methodology and an ongoing engineering refinement.
In designLocation signal noise (14%)Permission audit and IP variance components in design. PBS contribution shown separately, currently zero.
Out of scopeMobile advertising ID rotation (22%)Not currently shipped. Programmatic GAID rotation is not possible from a third-party app; user-initiated rotation guidance is on the roadmap. Excluded from PBS until built.
Out of scopeSocial media on-platform (9%)Off-platform pixels partially blocked today. Not currently addressed by dcoy. Excluded from PBS.
Out of scopeTransaction history (9%)Not currently addressed by dcoy. Excluded from PBS.
Current state · May 2026

PBS ranges by tier, four live layers contributing: Personal at 90 days: 38 to 48. Ghost at 90 days: 44 to 54 (weekly audit cadence). Blackout: not yet shipping; ranges to be published when the tier is live. Browser fingerprint noise injection is verified against EFF Cover Your Tracks on three of four sub-surfaces (5.1 of 6 points proven; canvas hash under investigation). Behavioral noise injection is live in production. Location signal rotation is in design.

04 · Competitive position

One score across every vector.

The consumer privacy market is populated by tools that each solve one piece of the problem, charge a premium for it, and provide no way to verify the result. The following comparison reflects three proven dcoy components against the competition's complete feature sets.

FeatureDeleteMeBlurPrivacy BeeNordVPNdcoy
Broker opt-out automationpartial
Repopulation monitoringpartial
Tracker SDK blockinglimited
Browser fingerprint noise injection✓ live
Behavioral noise injection✓ live
Monthly proof / audit score✓ Profile Blur Score
Pricing footnote

Competitor prices reflect publicly listed annual rates as of May 2026. dcoy: Personal $108/year, Ghost $228/year. Blackout coming soon.

05 · Background

The commercial surveillance profile.

What a profile is

A commercial surveillance profile is the aggregate of data points that surveillance pricing intermediaries, data brokers, and behavioral advertising platforms maintain about an individual. The FTC's January 2025 surveillance pricing study found that intermediary firms worked with at least 250 client businesses (grocers, apparel, health and beauty, home goods, convenience, and hardware retailers among them) using personal data to set targeted prices. Sources contributing to those profiles include:

Why existing tools are insufficient

The existing consumer privacy toolkit was designed for a desktop-first threat model built in the early 2010s. Modern surveillance infrastructure has evolved beyond it:

Blocking hides one session. It does nothing about the profile that already exists, the advertising ID that ties all app behavior together, or the tracker SDKs running inside ordinary apps. dcoy's approach is to degrade the existing profile while blocking the mechanisms that rebuild it.
06 · Platform architecture

Four coordinated layers.

dcoy attacks the surveillance profile through four coordinated layers. Layers 1, 2, and 3 are operational and contributing to the headline PBS. Layer 4 is the measurement layer.

Layer 1: Device-level identity noise · Live on desktop · Roadmap on mobile

On desktop, the Chrome extension performs page-level interception of canvas, WebGL, audio context, font enumeration, navigator properties, and WebRTC signals via main-world script injection. Three sub-surfaces are verified against EFF Cover Your Tracks weighting (WebGL renderer and hash, navigator JS surfaces, AudioContext). 5.1 of 6 PBS points are proven. The canvas hash sub-surface (0.9 pts) produces noisy output but EFF's reported hash has not yet differentiated; root cause is under investigation. Firefox is on the roadmap.

Mobile device-level identity noise is on the roadmap. Programmatic rotation of the Google Advertising ID is not possible from a third-party app; only the user (via device Settings) or the OS can reset it. A user-initiated rotation guidance flow with PBS attribution on confirmation is in design. iOS App Tracking Transparency audit is on the roadmap and will ship with the iOS build.

Current state · May 2026

Chrome extension v0.3.5 is live on the Chrome Web Store, reporting tracker and fingerprint blocks to the dcoy API every 5 minutes. Firefox port is on the roadmap. Android version 1.1.0 is live on the Google Play Store. iOS is scaffold only; full NetworkExtension and App Groups integration remains substantial development work and ships when ready.

Independent verification
  • EFF Cover Your Tracks: coveryourtracks.eff.org (Chrome extension fingerprint spoofing, three sub-surfaces verified)
  • For canvas hash sub-surface: verification in progress; current contribution honestly capped in dashboard

Layer 2: Network-layer tracker blocking · Proven

On Android, dcoy runs as a VpnService intercepting all device traffic and filtering it against a bundled blocklist of tracker SDK domains. Filtering uses DNS-over-HTTPS with a local resolver. No traffic is routed through dcoy servers. No root access is required.

On desktop, the Chrome extension blocks the same category of domains at the request level. iOS NetworkExtension filtering is on the roadmap and will ship with the iOS build. The current Android blocklist is a curated set focused on high-frequency consumer tracker SDKs; expansion via EasyPrivacy and Disconnect.me sourcing is on the roadmap.

Independent verification
  • The dcoy dashboard displays a real-time block log
  • Block counts are auditable from the log

Layer 3a: Cloud opt-out automation · Proven

dcoy's cloud agents submit CCPA deletion requests and GDPR erasure requests to a regularly updated list of consumer-facing data brokers on behalf of subscribers. The system monitors each broker for profile repopulation and resubmits when records reappear. This component is operational.

Current state · May 2026

The broker agent runs in production as a scheduled cron job on Render, with broker opt-out submissions and noise-injection events writing to the production database. The current rotation attempts approximately 30 brokers per cycle, with roughly 23 succeeding via web-form submission. Email-method brokers are queued for a future manual submission flow. Expansion of the broker list is the next phase of work.

Independent verification
  • Optery: optery.com
  • Privacy Rights Clearinghouse: privacyrights.org
  • Run an Optery scan before signup and after 90 days. The difference is the proof.

Layer 3b: Behavioral noise injection · Live

The behavioral noise component generates human-realistic browsing sessions whose interest categories are semantically inverse to the subscriber's real profile. The goal is to introduce enough contradictory signal that the ad platform's interest graph loses coherence, reducing its accuracy for targeting and pricing.

The architecture is as follows: a profile inversion engine computes the semantic opposite of the subscriber's Google Ad Center interest categories. A session simulator (Playwright-based headless browser) generates browsing sessions through residential proxy infrastructure, with variable scroll depth, dwell time, and interaction patterns designed to pass platform bot detection. A feedback loop monitors interest graph coherence to determine whether sessions are being counted or filtered.

Methodology

The current PBS contribution measures signals delivered against weekly target rate. Interest-graph coherence delta against a baseline is the target methodology and an ongoing engineering refinement. The injection architecture is live in production, no commodity privacy product ships this at consumer scale.

Current state · May 2026

Score computation is live in production since April 2026. Sessions and signals persist to the noise_injections table on every agent cycle. PBS contribution is non-zero and folded into the headline ranges.

Why we publish methodology: The measurement layer is the product. The way we calculate the behavioral contribution is open for inspection. The refinement path from signal-delivery to interest-graph coherence delta is engineering work, not a gating credibility question.

Layer 4: Measurement and audit · Live

Monthly, dcoy runs a full profile audit: checking Google My Ad Center and Meta Ad Preferences for assigned interest categories, querying our broker audit panel for records containing subscriber identifiers, and analysing tracker block log data. Browser fingerprint uniqueness is scored from EFF Cover Your Tracks sub-surface verification at 5.1 of 6 points proven. Every component feeds directly into the PBS calculation and is displayed in the subscriber dashboard with source links.

All four live components contribute their full calculated value. Location signal noise is in design and contributes zero until shipped.

07 · Vector weights

How the profile decomposes.

Vector weights reflect dcoy's own synthesis of proportional contribution to the total cross-platform commercial surveillance profile, informed by the FTC 6(b) Surveillance Pricing Study (January 2025), Princeton Web Transparency and Accountability Project research, EFF Cover Your Tracks, Dubé and Misra "Personalized Pricing and Consumer Welfare" (Journal of Political Economy, 2023), and Privacy Rights Clearinghouse data broker research. The percentages below are dcoy's own; the underlying sources informed but did not directly produce them.

VectorWeightPlatformStatusMethod
Data broker records28%AllLiveOpt-out automation + monitoring
Tracker SDK interception18%AllLiveExtension domain blocking
Browser fingerprint6%DesktopLiveMain-world JS noise injection; 5.1 of 6 pts proven, canvas under investigation
Behavioral noise injection12%AllLiveCloud agent noise injection, signals delivered against weekly target
Location data14%AllIn designPermission audit + IP variance
Mobile advertising ID (excluded)22%MobileOut of scopeNot currently shipped; user-guided rotation in design
Social media (excluded)9%ExcludedOut of scopeNot addressed by dcoy
Transaction history (excluded)9%ExcludedOut of scopeNot addressed by dcoy
08 · The Profile Blur Score

Calculation and ceilings.

Definition

The Profile Blur Score (PBS) is a 0 to 100 index expressing the degree to which a dcoy subscriber's commercial surveillance profile has been degraded relative to the profile an unprotected consumer of equivalent behaviour would generate in the same period. A PBS of 0 means the profile is fully intact. The Phase 1 ceiling is 78, reflecting the exclusion of mobile advertising ID (22%, not currently shipped), social media on-platform data (9%), and transaction history (9%), all disclosed in dashboard views.

All four live components contribute their calculated value to the headline PBS. Location signal noise is in design and contributes zero until shipped.

Current state · May 2026

Four components contribute to the headline PBS: broker removal (28 pts max), tracker SDK blocking (18 pts max), browser fingerprint noise injection (6 pts max; 5.1 currently proven against EFF; canvas hash 0.9 pts under investigation), and behavioral noise injection (12 pts max). Live component capacity totals 64. Location signal noise (14 pts max) is in design and contributes zero today; it is included in the Phase 1 ceiling as planned scope. The Phase 1 ceiling shown in the subscriber dashboard is 78, the sum of these five component maximums (64 points of live capacity plus 14 points of in-design location signal noise). The additional 22 points from mobile advertising ID remain excluded until that capability ships.

Component 1: Data broker audit · 28 points max · Live

Formula Broker component = (Records removed ÷ Records at baseline) × 28
Example: 34 records at baseline, 8 remaining at 90 days = (26 ÷ 34) × 28 = 21.4 points

Component 2: Tracker SDK blocking · 18 points max · Live

Percentage of known tracker SDK domain requests blocked over the prior 30-day period, drawn from the VPN/extension log.

Formula Tracker component = (Domains blocked ÷ Domains attempted) × 18

Component 3: Browser fingerprint · 6 points max · Live

Running in production on Chrome via main-world JS injection. Three sub-surfaces are verified against EFF Cover Your Tracks weighting (WebGL renderer and hash 2.2 pts, navigator JS surfaces 1.9 pts, AudioContext 1.0 pt). 5.1 of 6 points are proven. Canvas hash sub-surface (0.9 pts) is under investigation: wrappers fire and produce noisy output, but EFF's reported canvas hash has not yet differentiated.

Formula Fingerprint component = sum of verified sub-surface contributions (currently 5.1 / 6)
Current state · May 2026

Three sub-surfaces verified. 5.1 of 6 PBS points contributing to the headline. Canvas sub-surface (0.9 pts) under root cause investigation.

Component 4: Location signal noise · 14 points max · In design

Currently in design. The permission audit and IP variance components described elsewhere are the target architecture.

Target formula Location component = (Geolocation variance ratio × 0.6 + Permission audit score × 0.4) × 14
Current state · May 2026

This component is in design. PBS contribution is currently zero pending implementation. Headline PBS ranges in this document already exclude this component.

Component 5: Behavioral signal noise · 12 points max · Live

Running in production since April 2026. Score reflects signals delivered against a weekly target rate. The interest-graph coherence delta formula is the target methodology and an ongoing engineering refinement.

Current formula (live) Behavioral component = min(1, signals_delivered_7d ÷ target_rate_7d) × 12
Measures signals injected against a weekly target rate. Running in production.
Target formula (engineering refinement) Behavioral component = (1 − coherence_score) × 12
Will measure interest-graph coherence delta via cosine similarity between Google Ad Center category embeddings.

Total PBS formula

Total PBS = Broker + Tracker + Fingerprint + Behavioral
Location is in design and contributes zero until shipped.
Phase 1 ceiling (as rendered in subscriber dashboard): 78
Live component capacity: 64 (broker 28 + tracker 18 + fingerprint 6 + behavioral 12)
09 · Expected ranges by tier

Four live layers contributing.

The following ranges reflect all four live protection layers contributing to the headline PBS at Day 90. Location signal noise is in design and contributes zero until shipped.

Tier90-day PBSPrimary driverAudit cadence
Personal · $9/mo38 to 48Four live layers contributingMonthly
Ghost · $19/mo44 to 54Four live layers contributing, faster cadenceWeekly
Blackout · coming soonTo be published when tier ships--
Ranges reflect current state. Closing canvas hash verification (+0.9 pts) and shipping location signal noise (+up to 14 pts) would let your score reach more of the 78-point ceiling. Shipping mobile advertising ID rotation (+22 pts) would raise the ceiling itself.
10 · Independent verification

How any researcher can verify every live layer.

Every live PBS component is verifiable from outside dcoy's systems using free public tools. Broker removal via Optery, tracker blocking via dashboard log, browser fingerprint via EFF Cover Your Tracks (three of four sub-surfaces currently differentiable; 5.1 of 6 points proven), and behavioral noise injection via dashboard event log.

Data broker presence

Browser fingerprint

Tracker SDK blocking

Behavioral noise audit programme

dcoy is actively seeking credentialed journalists, academic researchers, and regulators to run controlled before-and-after audits of the behavioral noise component. We will provide free Ghost-tier access for the duration of the study. Results will be published in full: positive, negative, or inconclusive.

To apply for research access, contact us. The methodology is public. The session architecture is described in full in this document. We invite independent replication.
11 · Legal and ethical framework

Is this legal?

Yes. Every action dcoy takes operates on the user's own device, within their own accounts, and exercises rights they already hold:

Claims accuracy

PBS ranges published in dcoy's marketing (38 to 48 Personal, 44 to 54 Ghost) reflect all four live protection layers contributing to the headline score: broker removal, tracker SDK blocking, browser fingerprint noise injection (5.1 of 6 points proven; canvas hash sub-surface under investigation), and behavioral noise injection. Location signal rotation is in design and contributes zero until shipped. Mobile advertising ID rotation is not currently shipped and is excluded from PBS.

dcoy does not claim to eliminate surveillance, defeat all tracking, or guarantee any specific outcome. The PBS measures what is measurable. It discloses what is not yet proven. That honesty is the product.

12 · Conclusion

Not with assertions. With numbers.

The surveillance industry built a machine to make individuals legible to institutions. dcoy runs the same logic in the opposite direction, making individuals illegible, continuously. Four components are live and contributing to the headline PBS today: broker removal, tracker SDK blocking, browser fingerprint noise injection on Chrome (5.1 of 6 points proven against EFF Cover Your Tracks; canvas hash sub-surface under investigation), and behavioral noise injection. Location signal rotation is in design. Mobile advertising ID rotation is excluded from PBS until a user-guided flow ships. The roadmap is clear.

The Profile Blur Score is how we prove it. Not with assertions. With numbers. With auditable formulas. With verification tools anyone can run. With a dashboard that shows the before and the after, every month, linked to the public sources that feed it. Every claim has a verification path, and the methodology is published in full.

Every other privacy product asks you to trust them. We built the score so you don't have to.

Read the methodology, then try it
Privacy you can measure.

The methodology is public. The architecture is described in full above. We invite independent replication.