Data Masking

Data Masking
Data Masking

In this article we will talk about Data Masking, and in previous article we already discussed about Network Disasters.

Data masking

Data masking technology secures data by replacing sensitive information with a non-sensitive version. The non-sensitive version looks and acts like the original. This means that a business process can use non-sensitive data and there is no need to change the supporting applications or data storage facilities. In the most common use case, masking limits the propagation of sensitive data within IT systems by distributing surrogate data sets for testing and analysis. Information can be dynamically masked if the system or application determines that a user request for sensitive information is risky.

Data masking can replace sensitive data in non-production environments to protect the underlying information.

There are several data masking techniques that can ensure that data remains meaningful but changed enough to protect it.

  • Substitution replaces data with authentic looking values to apply anonymity to the data records.
  • Shuffling derives a substitution set from the same column of data that a user wants to mask. This technique works well for financial information in a test database, for example.
  • Nulling out applies a null value to a particular field, which completely prevents visibility of the data.

Data obfuscation is the use and practice of data masking and steganography techniques in the cybersecurity and cyber intelligence profession. Obfuscation is the art of making the message confusing, ambiguous, or harder to understand. A system may purposely scramble messages to prevent unauthorized access to sensitive information.

Steganalysis is the discovery that hidden information exists. The goal of steganalysis is to discover the hidden information.

Patterns in the stego-image create suspicion. For example, a disk may have unused areas that hide information. Disk analysis utilities can report on hidden information in unused clusters of storage devices. Filters can capture data packets that contain hidden information in packet headers. Both of these methods are using steganography signatures.

By comparing an original image with the stego-image, an analyst may pick up repetitive patterns visually.

Data obfuscation

Software watermarking protects software from unauthorized access or modification. Software watermarking inserts a secret message into the program as proof of ownership. The secret message is the software watermark. If someone tries to remove the watermark, the result is nonfunctional code.

Software obfuscation translates software into a version equivalent to the original but one that is harder for attackers to analyze. Trying to reverse engineer the software gives unintelligible results from software that still functions.

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