Data anonymization Puns

Hey Reddit , 🙌

As a DevsecOps I was lacking tools to secure MongoDB databases.

I was always think, what would happen to my team if the company database got leaked.

To solve this, with Nabil my co-founder, we created ReflectDB a tool to help you secure your MongoDB databases.

Our vision is to help developers work better while maximizing data privacy.

Our main feature is real-time data anonymization (MongoDB only).

It allows developers to access production data without any risk of data leak or GDPR noncompliance (like having sensitive customer data stored on your dev team computers). It also means that you don’t have to write an anonymization script or anonymize dumps of your database, ReflectDB does it for you when you need it.

Other features we developed:

-MFA authentication

-Rate-limit to avoid database dumps

-Real-time monitoring to detect suspicious behaviors

-Instant Slack notifications to approve/disapprove requests on the database

Thank you for your attention.

What do you think? Please give us honest feedback! :)

reflectdb.net/

I am not Very Sure how GDPR regulation can be followed in Power BI ...anonymization is an issue in Power Bi When Reading data from Different Regions.

Not really sure where to post, so feel free to point me elsewhere. Basically I'm curious: how could one collect user data anonymously, but also use that data to enhance a user's experience?

For example, say Amazon has my order history and wishes to use it to extract meaningful statistics from it to sell me more things or whatever, how could they anonymize my data for processing so that my history/buying habits stay private, but still use the insight gleaned from the processing to sell me more things, etc.?

And please feel free to get technical as I'm looking to fully understand if this is possible, and if so, how.

Thanks!

We are happy to announce that Anonymization plugin is available now. To get it, we invite you to purchase GLPI Network Subscription (if you use GLPI on-premises) or use GLPI Network Cloud platform (the plugin is already pre-installed and included in our offer).

>This plugin will allow the data anonymization in GLPI, directly from the web interface or with the command line, either unitarily or massively.

To learn more about its features and configuration, please, read the documentation: click here

In case if you want to test the Anonymization plugin we offer 45 days free trial on GLPI Network Cloud, just register your account here and instantly access your virtual instance: https://myaccount.glpi-network.cloud/register.php

Hope this is not off-topic in this group... I'm looking for some help to get started on the topic of data anonymization: tools, techniques, algorithms etc. I'm an advanced Python user, but no R skills. Appreciate any pointers.

Hi All I reposted this question because my previous question I think no one answered

I want to create a python script that can mask/anonymize the information inside each CSV column without removing its content. Because the data will be used for further analysis and doing some statistical modelling. The data mostly contain user ID, project ID, Customer ID, address of the customer, name of the customer, order type, email address. I'm kinda stuck on the current progress as I wanted to make this process more effective

1. How could I do this process more scalable, meaning I don't need to create a script for each CSV file but more into how could I use some technique to apply the script to every CSV files without rewriting from scratch?

My current approach: My approach right now is by dealing on each column one by one by doing something on it. For example the user ID, I replaced it with the additional string in front of the unique value ( for example since user ID 1234 in the first row, it gets replaced by user_0).

Please give me some advice and I would like to discuss so that I can do a more effective way

Edit: This how the data looks like (I hope I put it in the allowable format)

plantid projectid plant_name    project_name                  address         customerid projecttype
15052.0  6496     Manufacturing ASAHI,PT-PRO/PTN/06-2012/192  streetname-city e8cfa43f   Individual
15052.0  6458     Manufacturing CIMB NIAGA-PRO/PTN/06-2012/174 streetname-city 7b2bf5dc  Individual
15052.0  11441    Manufacturing DM STOCK 2015                 streetname-city dc0c9893   Corporate

And this is my current code

data['customer_id'] = 'user_' + (pd.Series(pd.factorize(data['customer_id'])[0] + 1)).astype(str)

data['project_id'] = 'Project_' + (pd.Series(pd.factorize(data['project_id'])[0] + 1)).astype(str)

https://www.spiritlegal.com/en/news/details/e-commerce-retail-facebook-custom-audience-not-allowed-without-consent.html#practical

This could screw over a lot of EU based companies and software platforms that hash data for anonymization. IIRC, the ICO even released a compliancy guide stating that hashing data would be fine to meet the requirements of erasure (SHA-256 was even explicitly mentioned as an acceptable method, I think).

Also, this was for the old Germany data protection law... however, I picture this holding true for the GDPR and don't see a reason that it wouldn't hold true. Based on Google searching, looks like the ruling came out last week (September 13th, 2018). Could be interesting. Thoughts?