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Վերադառնալ բլոգինGDPR & Համապատասխանություն

Անանունացում կամ կեղծանունացում. ռիսկ 20 մլն եվրո

GDPR-ն հիմնովին տարբեր կերպ է դիտում անանունացված ու կեղծանունացված տվյալները: Իրական անանունացումն ամբողջությամբ վերացնում է GDPR-ի ոլորտը: Կեղծանունացումը GDPR-ի ոլորտն է պահում:

May 8, 20268 րոպե կարդալ
GDPR anonymization pseudonymizationArticle 4 recital 26personal data scope20 million EUR fineanonymization compliance determination

Անանունացում կամ կեղծանունացում. ռիսկ 20 մլն եվրո

83-րդ հոդվածն ամրագրում է առավելագույն տուգanqner 20 mln evro kamnkam globalain tarvayin yejekhtin 4%-i chafov: Mek iravakan harts varumа ayт risky. kirarutyan masunerу: Ot andzi vray hy:

Աnanunacumy veratsnum e olortey: Kegzanunacsumы chheq: Ayd baky mets e:

Yerku srbagrum` pastabanakan ezqov

26-rd Recital-y sazum e ananunacsutyan standarty: Andzы petk e liner "hnaravor che stanum hnaravor" identificacnan: Texumy lain e: Ayն enkalnum e "hnakabarevapi" karoghutyan akanatarn: Sary inchpes karogh e aynt vorpes controlelr-y: Aynt nayev enkalnum e ayadz mshakutsoghy ev ayadz yerrord koxy:

4(5)-rd hodvatsы srbagrum e kegzanunacumy: Failerы kegzanunacvats en, erb banaliyi voghoghutyamb karog en hetdzenvel: Bazrel banaliny, dzerqum e dery tavy tvealnery: Ayт lratsatsich tevalnery petk e aratznhatum pahel: Ayd ananunacsutyan che:

Kegzanunacvats eghanaknery dery andznadzdzdnan e: Orenqy lriv kazelum e: Olortay artatonutyun chka: Lriv karger:

Skhaly petakannishany ineche qartsinum

Kegzanunacvats bazmy ananan votsin petakannishaneli dnem e hajtum e hing khndri gtnum e mekanutyamb:

  • Skhaly ROPA entryner 30-rd hodvatsov
  • Subject iravunqneri gortsinteri batsaknery tarmalelu, ambagjvelitselu ev krepavorelu hamar
  • Pahelu jadqagrakan chadagragir chka — veractsu gortsetich che goyutyun chunи
  • Fayelbanutyan handartumnery sahmananvar ashkhati hamar
  • Handanelu uzhi hamar veracanelutyan uytyun chka

Yuraqanchiur baky arachhin ev verji khakhtutyun e: Boly hinge mtnum e mek pipline-um:

2025-i veradzernakhabi nshan

2025 tvakanum EDPB-y hamakargvats vertadzernakhabi varzhutyun anvets: Zekuytsy anvanets mekik kerber kovandkum gtnvats tarat. "Kagnatsman artakuthyamp ogtagurvats anavorinakan ananunacsutyan metoter:" DPA-nerы hima veratzern en ananunacsutyan orakutyamb: Nrank veranayum en aveliny avely, qan mijain arveq kangnumn e: Qayle petk e ashkhatvi:

Tokenized bazan khndzaryum banalinov kegzanunacvats e: Ayd anannunacvats che: Aynt banalin ka: Banaliny kargo e hetdzel: Anonanoum ands kochel e hangist hatkov 2025-i zekuytsy nkaragir tvarky:

Chchi metodы chambarev ushiratsnel

Irakanum ananunacsutyan — olortits arts: Ogtagortsir Redact: PII-n gnum e, kayt uytyun chуни: Karo naev katarelukyan hash el en yetkin bardzr-entropia arzheknerov bnakanich yelovutyany: Kavaragrel hravarutyuny: Iravakan partavarutyunner ardustic nerin zervum chen:

Kegzanunacutyun — olortum: Ogtagortsir Replace, Mask kamnkam Encrypt: Orenqy lriv kazelum e: Kegzanunacumы vnasmits kayts e zijalume: Ayv chyi kayts e iravakan partavarutyunnery:

Karavarum verkadadardzeli — hetazotutyan ev veradzernakhabi hamar: Ogtagortsir Encrypt klientum pahvats banalinnerov: Banalin pahеly petk e bavarakanarchi EDPB 05/2022 banalin bazhanmany kanonnerin: Chshmarutyuny andradznoreel DPIA-um:

Irastes gumanardutyan taratsq

My ynkeryutyun "anananuncvats" hahakovakan tarery verkum e hetazotoghnerein: Nrank kirazel en Redact metody: PII-n gnum e: Tojeni adzyak chka: Khetadzutyan vudka chka:

DPO-n sranits astumy DPIA-um: Kirazvatz metody: Bnoroshich tesahnery: Inchvov khetradum chуникаlterumi: Meналtsi risqi maki: Arduny olorti artits ynknum e: Subject iravunqnery ev fayelbanutyan kanonnery khzoghum chen hetazotakan ptiknerov:

Metody hamapatasmun e pnutsumhim: Ayd chashkhatume veranumays e: Kiyakhvum e veradzernakabanutyan jamanak:

Ints hamar e gavanakanagrum e record-y

My ynkeryutyun ayspisi che karoghi petaky ananunacsutyan pntsel: Pahanjum e zavakagurvats: DPIA-y petk e cuyts ta chors ban: Qanzi bnoroshichnery enkalvum en: Qanzi methody kirazvatz e: Ints havov khetadum uzhi zovk chкa: Ints e mналtsyal risqi maky:

Ay record-ic ayspisi, haskagrutyan hamar GDPR-i irovakan harimner ogtagortsoghy katary data-set-ы olortum e: Partavarutyunnery lriv gandum en: ROPA entryy petk e goyutуn unenа: Fayelbanutyan handartumnery petk e goyutyun unenа: Handanelu uzhin petk e goyutyun unenа: Areats partavarutyunner vertsum chen aranc apatsuytsы:

Inchpisi e handaneluyi iravunqnery anananuncvatz eghanaknerov kap unen, tes GDPR handanelu iravunq ev EDPB 2025 uzhecuyts: Fayelbanutyan kanonnerы sazmanikov sahmanapandak faylerov kiskumanum, tes Data fayelbanutyan hamapataskhanutyan ev TikTok-i tugankа:

Aghbyurner

Հոդվածներ, որոնք կապված են

GDPR & Համապատասխանություն

Japan My Number: Verhoeff & APPI

63% of generic tools fail My Number detection in Japanese documents. My Number uses Verhoeff algorithm — the most complex national ID checksum in Asia.

GDPR & Համապատասխանություն

HDPA Greece: AFM & AMKA Detection

Greek AFM detected with 52% accuracy by generic tools. HDPA issued 89 decisions in 2024 — up 162% from 2022. Tourism and maritime sectors face distinct.

GDPR & Համապատասխանություն

NAIH Hungary: TAJ-Szám and Adóazonosító Jel

Hungarian NER accuracy is 67% vs. EU average 82% — NAIH's 2024 assessment. TAJ-szám weighted checksum and adóazonosító jel detection gaps.

Պատրաստ եք պաշտպանելու ձեր տվյալները?

Սկսեք PII անանոնիմացնել 285+ կազմակերպության տեսակներով 48 լեզուներով:

Սկսեք անվճար փորձաշրջանԴիտել առանձնահատկությունները

About this page

We update this page when our platform or the law changes.

Read our founder note for how we work.

Each change shows up in the timestamp at the top.

Related reading

We follow these rules

  • GDPR (EU 2016/679).
  • ISO/IEC 27001:2022.
  • NIS2 (EU 2022/2555).
  • HIPAA safe harbor under 45 CFR § 164.514(b)(2).

Our promise

We do not sell your data.

We do not train models on your text.

We store your files in Germany.

You can delete your account at any time.

You own your work.

Where we run

Our servers live in Falkenstein, Germany.

We use Hetzner. They hold ISO 27001 certification.

All data stays in the EU.

Backups run every day.

Need help?

Email support@anonym.legal.

We reply within one business day.

How we test

We run a full check suite on every release.

Each surface gets its own sweep script and report.

Human reviewers spot-check the output each week.

We track recall and precision on a labelled set.

Bad runs block the deploy.

What we never do

  • We never sell your information to third parties.
  • We never train models on what you upload.
  • We never keep your work after you delete it.
  • We never share keys with any outside firm.
  • We never run ads inside the product.

Plans in plain words

We sell credits, not seats.

One credit covers one short job.

Long jobs use a few credits each.

You can top up at any time.

Unused credits roll over each month.

Read the plans page for current rates.

Who built this

A small team of engineers and lawyers built this.

We ship from Europe and work in the open.

Our founder note spells out why we started.

Where to start

How the parts fit

A browser add-on cleans text inside Chrome.

A Word plug-in handles drafts in Office.

A small desktop tool works on whole folders.

An agent protocol link feeds large models safely.

All four share one core engine and one rule set.

Words from our team

We started this work after a lunch about cookies.

One friend kept getting odd ads on her phone.

We asked why a court file leaked through a draft.

We sketched the first build on a napkin that week.

By month three we had a tiny demo for a friend.

She used it on her first case the next day.

Common questions we hear

Can the tool read scanned PDFs? Yes, with OCR.

Does it work on long files? Yes, in small chunks.

Can I roll my own rule set? Yes, save it as a preset.

Does it run offline? The desktop build runs offline.

Do you keep my files? No, the cloud build wipes after each run.

Will it learn from my work? No, we never train on inputs.

A short tour of the workflow

Upload a file or paste a snippet of prose.

Pick the entities you want gone from the draft.

Choose a method: replace, mask, hash, encrypt, or redact.

Press run and watch the side panel show each hit.

Skim the result and tweak any rule that misfired.

Save the cleaned file or send it to a teammate.