Ensuring Data Integrity via Checks, Tests, and Best Practices

Monday, June 04, 2012

Fergal Glynn

68b48711426f3b082ab24e5746a66b36

What is Data Integrity? Learn How to Ensure Database Data Integrity via Checks, Tests, & Best Practices

Data integrity is a fundamental component of information security. In its broadest use, “data integrity” refers to the accuracy and consistency of data stored in a database, data warehouse, data mart or other construct.

The term – Data Integrity – can be used to describe a state, a process or a function – and is often used as a proxy for “data quality”.

Data with “integrity” is said to have a complete or whole structure. Data values are standardized according to a data model and/or data type. All characteristics of the data must be correct – including business rules, relations, dates, definitions and lineage – for data to be complete.

Data integrity is imposed within a database when it is designed and is authenticated through the ongoing use of error checking and validation routines. As a simple example, to maintain data integrity numeric columns/cells should not accept alphabetic data.

As a process, data integrity verifies that data has remained unaltered in transit from creation to reception. As a state or condition, Data Integrity is a measure of the validity and fidelity of a data object. As a function related to security, a data integrity service maintains information exactly as it was inputted, and is auditable to affirm its reliability.

Data undergoes any number of operations in support of decision-making, such as capture, storage, retrieval, update and transfer. Data integrity can also be a performance measure during these operations based on the detected error rate.

Data must be kept free from corruption, modification or unauthorized disclosure to drive any number of mission-critical business processes with accuracy. Inaccuracies can occur either accidentally (e.g .through programming errors), or maliciously (e.g. through breaches or hacks).

Database security professionals employ any number of practices to assure data integrity, including:

  • Data encryption, which locks data by cipher
  • Data backup, which stores a copy of data in an alternate location
  • Access controls, including assignment of read/write privileges
  • Input validation, to prevent incorrect data entry
  • Data validation, to certify uncorrupted transmission

Software developers must also be concerned with data integrity. They can define integrity constraints to enforce business rules on data when entered into an application.

Business rules specify conditions and relationships that must always be true, or must always be false. When a data integrity constraint is applied to a database table, all data in the table must conform to the corresponding rule.

Cross-posted from Veracode

Possibly Related Articles:
21418
General
Information Security
Encryption Testing Databases Access Control Data Classification Best Practices Backups Security Audits Data Integrity
Post Rating I Like this!
The views expressed in this post are the opinions of the Infosec Island member that posted this content. Infosec Island is not responsible for the content or messaging of this post.

Unauthorized reproduction of this article (in part or in whole) is prohibited without the express written permission of Infosec Island and the Infosec Island member that posted this content--this includes using our RSS feed for any purpose other than personal use.