Data classification is an essential component of any data security and compliance program, particularly if your company keeps large amounts of data. It lays the groundwork for your data security strategy by helping you in determining where you keep sensitive and regulated data, both on-premises and in the cloud. Furthermore, data classification enhances user productivity and decision-making while reducing storage and maintenance costs by removing unnecessary data.
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Definitions and Terms Used in Data Classification
The practice of organizing structured and unstructured data into defined categories that reflect distinct types of data is known as data categorization. Among the standard classifications used in data categorization are:
- Public
- Confidential
- Sensitive
- Personal
Sensitive data is a broad word that refers to data that is restricted for use by specified individuals or groups. The terms “sensitive data” and “confidential data” are frequently used interchangeably. Intellectual property and trade secrets are examples of sensitive data.
Data reclassification is the process of re-categorizing data in order to apply relevant updates, such as changes in legal or contractual requirements, data usage or value, or new or revised regulations.
Objective of Data Classification
Data classification helps you in understanding what types of data you store and where that data is stored. This involves:
- Informs risk management, judicial discovery, and regulatory compliance processes.
- Helps in prioritizing security measures
- By speeding search and e-discovery, it increases user productivity and decision-making.
- Reduces data management and storage costs by identifying duplicate and outdated data.
- Helps IT teams in justifying requests for data security investments.
Types of Data Classification
Data classification can be done using content, context, or user selections:
- Content-based classification includes analyzing and categorizing files and documents.
- Context-based classification comprises categorizing files based on metadata such as the application that created the file (for example, online accounting), the person who created the document (for example, finance personnel), or the location where the files were created or edited (for example, finance or legal department buildings).
- User-based classification includes categorizing files based on the manual judgment of a skilled user. Individuals who deal with documents can indicate their level of sensitivity when they generate the document, after a significant update or review, or before the content is distributed.
Determining Data Risk
Apart from classification types, it is essential for an organization to compare the overall risk associated with the types of data, how that data is managed, and where it is stored/sent (endpoints). It is common practice to classify systems and data into three levels of risk.
- Low risk: If the data is public and not easily lost (e.g., recovery is simple), this data collection and the systems that surround it are likely to be less risky than others.
- Moderate risk: This is data that is not publicly available or is only used internally (by your business and/or partners). However, it is unlikely to be too important to operations or sensitive to be classified as “high risk.” Proprietary operating processes, cost of goods, and some company paperwork may be classified as moderate.
- High risk: Anything remotely sensitive or crucial to operational security is classified as high risk. Furthermore, data that is incredibly difficult to recover (if lost). All secret, sensitive, and necessary data is classified as high risk.
Note: Some use a more detailed scale, adding “severe” risk or other classifications to help differentiate data.
Benefits of Data Classification
Consistent usage of data classification will allow for more effective business operations while also lowering the expenses of providing acceptable information security. By classifying the data, your company can be better prepared to determine the risk and effect of an incident based on the type of data involved.
Compliance
Classifying data, adding labels, and enforcing regulations all contribute to your organization’s ability to meet legal and regulatory obligations (GDPR).
Usage Control
Understanding the sensitivity of the data allows you to determine who should and should not have access to it both within and outside of your organization.
Awareness
Employees are better aware of the type of information they are interacting with and its value, as well as their responsibility to protect it in order to prevent data loss or damage to intellectual property. It also enhances data security knowledge and determines the business impact of a data breach, ransomware attack, or other threats.
End-User Participation
By empowering its users, data classification brings security to the forefront of your organization. Many data leaks could be averted with the use of a data classification system. Adding visual labels to headers and footers raises end-user awareness and supports them in becoming more security-minded and avoiding sharing sensitive content on USB drives, over e-mail, or cloud services such as Box or Dropbox.
Developing an Efficient Data Classification Policy
A data classification policy is a document that comprises a classification framework, a set of responsibilities for detecting sensitive data, and definitions of the various levels of data classification.
An effective classification policy:
- Uses criteria that are simple and eliminate ambiguity, yet are general enough to apply to a variety of data sets and contexts.
- Is easy to understand and written in plain language
- corresponds to the organization’s business
- Is limited to three or four classification levels
- It includes a point of contact for clarification.
- Creates a review schedule
Data classification might come under the information creators, subject matter experts, or those accountable for data accuracy.
The policy also specifies the data classification process, including how frequently data classification should occur, for what data, which style of data classification is appropriate for different categories of data, and what technical means should be used to classify data. The data classification policy is a component of the overall information security policy, which describes how sensitive data should be protected.
Conclusion
Data security is becoming increasingly difficult, yet small measures are essential for an ordered and classified data model. Data classification gives a clear image of all data under an organization’s control, as well as an understanding of where data is maintained, how to access it conveniently, and the best method to secure it from potential security hazards. Data classification, once established, provides an ordered framework that permits more adequate data protection procedures and encourages employee compliance with security regulations.
