By · Last updated 2026-04-07

5 Metode Anonimisasi

Pilih metode perlindungan yang tepat untuk persyaratan kepatuhan Anda. Dari redaksi lengkap hingga enkripsi yang dapat dibalik, kami siap membantu Anda.

Ganti

Gantikan PII yang terdeteksi dengan data palsu yang realistis yang mempertahankan keterbacaan dokumen.

Terbaik Untuk:

  • Lingkungan pengujian
  • Generasi data demo
  • Dataset pelatihan
  • Berbagi dokumen

Contoh

Sebelum
Hubungi John Smith di john.smith@company.com
Setelah
Hubungi Jane Doe di jane.doe@example.com

Redaksi

Hapus sepenuhnya PII dari dokumen, menggantinya dengan placeholder seperti [REDACTED].

Terbaik Untuk:

  • Dokumen hukum
  • Permintaan FOIA
  • Catatan publik
  • Pengajuan pengadilan

Contoh

Sebelum
Hubungi John Smith di john.smith@company.com
Setelah
Hubungi [REDACTED] di [REDACTED]

Hash (SHA-256)

Hash kriptografi satu arah yang memungkinkan pseudonimisasi yang konsisten di seluruh dokumen.

Terbaik Untuk:

  • Data penelitian
  • Analitik
  • Tautan antar dokumen
  • Pseudonimisasi

Contoh

Sebelum
Hubungi John Smith di john.smith@company.com
Setelah
Hubungi a1b2c3d4 di e5f6g7h8

Enkripsi (AES-256-GCM)

Enkripsi yang dapat dibalik yang memungkinkan pengguna yang berwenang untuk memulihkan data asli dengan kunci yang benar.

Terbaik Untuk:

  • Anonimisasi sementara
  • Kebutuhan pemulihan data
  • Persyaratan audit
  • Alur kerja yang dapat dibalik

Contoh

Sebelum
Hubungi John Smith di john.smith@company.com
Setelah
Hubungi [ENC:xyz123] di [ENC:abc456]

Mask

Sebagian menyembunyikan PII sambil mempertahankan beberapa karakter terlihat untuk referensi.

Terbaik Untuk:

  • Dukungan pelanggan
  • Tampilan verifikasi
  • Kebutuhan visibilitas sebagian
  • Antarmuka pengguna

Contoh

Sebelum
Hubungi John Smith di john.smith@company.com
Setelah
Hubungi J*** S**** di j***.s****@c******.com

Perbandingan Metode

MetodeDapat DibalikDapat DihubungkanDapat DibacaTerbaik Untuk
GantiTidakTidakYaPengujian, Demo
RedaksiTidakTidakSebagianHukum, Catatan Publik
Hash (SHA-256)TidakYaTidakPenelitian, Analitik
Enkripsi (AES-256-GCM)YaTidakTidakSementara, Audit
MaskSebagianTidakSebagianDukungan, Tampilan UI

Coba Semua Metode Gratis

Mulai dengan 200 token gratis per siklus. Bereksperimenlah dengan semua metode anonimisasi.

Buat Akun Gratis

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.