Masking XML And CSV Stored in S3 Backets

Masking XML And CSV Stored in S3 Backets

Amazon Simple Storage Service (Amazon S3) is an object storage service host by Amazon which is widely used nowadays for storing data of any structure. It supports numerous use cases beginning from archiving miscellaneous files and documents, storing websites data and ending with data storage for Machine Learning and Big Data analytics.

XML format is a common way to represent naturally hierarchical data or the entire business objects. These types of data in most cases are the bane of “table” approach and make it difficult and resource-consuming when it comes to storing its data in relational databases. This is where S3 shines and can provide companies with the economic and safe solution for storing such types of data. However, it is always good to think about protection of such data inside the S3 bucket, bringing your data security to the next level. So that no one can damage your business by manipulating and getting your data.

With this major update in DataSunrise Security you can introduce an additional layer of protection to your data stored at S3 buckets by applying Dynamic Data Masking. It is supported now for the XML files, along with CSV and JSON formats support, making it extremely useful to secure S3 buckets used in your BI, ML and other solutions. Protect your data by applying Dynamic Masking rules, to replace your data on the fly with the values you define without changing the initial files.

The Rule’s settings and result of XML masking:


<people_test>
    <record>
        <id>1</id>
        <first_name>********</first_name>
        <last_name>*****</last_name>
        <email>tguess0@washington.edu</email>
        <gender>Male</gender>
        <ip_address>181.236.58.217</ip_address>
    </record>
    <record>
        <id>2</id>
        <first_name>*******</first_name>
        <last_name>******</last_name>
        <email>wculpan1@nature.com</email>
        <gender>Male</gender>
        <ip_address>201.187.144.70</ip_address>
    </record>
    <record>
        <id>3</id>
        <first_name>*******</first_name>
        <last_name>****</last_name>
        <email>klace2@etsy.com</email>
        <gender>Female</gender>
        <ip_address>113.21.227.26</ip_address>
    </record>
</people_test>

The Rule’s settings and result of CSV masking:


id    first_name    last_name    email    gender    ip_address
*     Gilfoyle      *********    *****    Female    **********
*     Chilcotte     *********    *****    Male      **********
*     Terrell       *********    *****    Male      **********
*     Pearle        *********    *****    Female    **********
*     Kits          *********    *****    Male      **********
*     McAlpine      *********    *****    Male      **********
Download free 30 days Trial