Consider you’re the CISO of an organization of 10,000 employees that creates millions of documents and emails daily, some of which are highly sensitive and may lead to a headline-making breach and seven-figure fines. Although much of the data created every day could be published directly on the front page of the newspaper, there are a few exceptions.
As long as you don’t know what information must be protected at the level of military-grade security, it is difficult to prioritize risk mitigation and comply with privacy laws. Data classification is the solution to this problem.
What Is Data Classification?
During data classification, you evaluate unstructured and structured data and classify them according to information about the contents, file types, and metadata.
Data classification enables organizations to answer important questions about their data, which can help mitigate risks and manage data governance policies. In order to comply with current data privacy regulations, a comprehensive data classification is necessary (but not sufficient). It can also tell you what types of sensitive data your users might create.
Data Sensitivity Levels
There are three classification levels for data sensitivity: high, medium, and low.
High Sensitivity Data
The organization or individuals would suffer catastrophic consequences if their data is compromised or destroyed in an unauthorized transaction. We can classify data based on a variety of factors, including financial records, intellectual property, and authenticity.
Medium Sensitivity Data
Compromise or destruction would not cause catastrophic damage to the organization or individuals if intended only for internal use. Examples: Documents and emails without any confidential information.
Low Sensitivity Data
Public access to them is intended. Examples include the content of public websites.
To know more about what security steps to take after being affected by a data breach, visit our blog.
Types of Data Classification
There are multiple markers that describe the types of data as well as their integrity and confidentiality. Availability is equally an important consideration when classifying data. In many cases, data sensitivity is classified based on levels of importance or privacy. It depends on the security measures implemented to protect each classification level.
There are mainly three types of data classification:
- The content-based classification process consists of analyzing and interpreting files in search of sensitive information.
- A contextual-based classification incorporates characteristics such as creator, application, and location as indirect markers.
- A user-based classification is a process based on the manual selection of each document. During creation, editing, or reviewing sensitive flag documents, user-based classification relies on the user’s knowledge and discretion.
The firm needs to determine the types of content, context, and user-based approaches.
Determining the Risk of Data
In addition to classifying data types, a company needs to assess how(endpoints) and where(storage) types of data are handled. A common practice is to separate data and systems into three levels of risk.
- Low threat: It is likely to be safer to collect public data and use its associated systems if public data is easily accessible and not easily lost (e.g., easy to recover).
- Moderate risk: Company data is not publicly available and is only available internally to the company and its partners. It may also not be too sensitive to be considered “high risk.” Moderate items include internal operating procedures, costs of goods, and some company documents.
- Risky data is data that is extremely hard to recover (if lost). Also, information that is remotely sensitive or vital to operational security. All types of data that are sharp and essential can be classified as high risk.
Data Classification Best Practices
Follow these best practices as you implement and execute your data classification policy.
- Your classification plan should take into account any relevant compliance regulations or privacy laws applicable to your organization
- Make sure your scope is realistic (don’t boil the ocean) and also clearly defined patterns (like PCI-DSS)
- Automate data processing to handle large volumes of data efficiently
- Consider creating custom classification rules when necessary, but do not reinvent the wheel
- Make necessary adjustments to classification rules/levels
- Make sure your classification results are accurate
- Analyze your results and determine the best way to utilize them, from business intelligence to data security
Lastly, the classification of data is a fundamental component of any security program. In a nutshell, it outlines how IT security is integrated with information security, protecting your firm’s most sensitive information.
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