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Data Classification: Overview, Types, and Examples
Data classification defines and categorizes business data, information, and files. It is used by organizations that are required to follow stringent compliance guidelines. The primary purpose of data classification is to understand the sensitivity of stored information to build a robust security system using the right cybersecurity tools.
By classifying data, organizations can determine the following −
Who is authorized to access specific data?
What protection policies to use for storing and transferring those data?
What are regulatory standards applicable to specific data?
Data classification empowers an organization to manage its data with privacy, secured by cyberattacks, and in compliance with regulatory standards.
Types of Data Classification
Data can be classified into three types,
Content-based Classification − Classifying data based on their content, such as files, format type, etc.
Context-based Classification − Classifying data based on Metadata such as the application used to create a file, the person who made the document, or the location of the data.
User-based Classification − Classifying data based on the personal judgment of the user. You can classify the data using your decision.
Data Sensitivity Levels
You can assign sensitivity levels to data and determine their value.
High sensitive data − It includes data that can have a catastrophic impact on the organization if they are compromised, deleted, or falls into the hand of hackers. This could consist of financial records, authentication data, and intellectual property.
Example − Suppose your company collects credit card information from customers buying products or services. Data like this should follow strict authorization controls, encryption, and stringent auditing for detecting access requests. A data breach is likely to ruin the reputation of the organization and can cost a significant financial loss.
Medium sensitivity data − These data are only for internal use but can significantly impact the organization or the individual if compromised or destroyed. This includes emails, documents, and files with no high-sensitive data.
Example − Whenever you deal with a third-party vendor, you involve in a contract containing signatures of the agreement. Although a breach of these data may not harm your customers, it can divulge sensitive information about your business details.
Low-sensitive data − It is intended for public use, such as the content on a public website.
Example − You upload content, such as blogs, pictures, etc., on your website for marketing purposes. These data are not highly sensitive, so you may not need strict controls as it is publicly available for audiences.
Data Classification Levels
Once you determine the sensitivity of the data, you need to assign levels to these data that answer the questions −
Who can access these data?
How long do these data need to stay in the system?
Levels of data classification
Public data − These data are accessible to the public and are freely used, shared, and reused without any legal persecution.
Example − first and last name of an individual, job descriptions, press releases, etc.
Internal-only data − These are accessible only to specific personnel or employees of an organization who are given special access.
Examples − Internal memos, internal communications, marketing plans, etc.
Confidential data − Accessibility is only granted through special authorization or clearance.
Examples − Cardholder data, social security numbers, data protected under HIPPA, PCI DSS, etc.
Restricted data − Unauthorized access to these data leads to massive legal fines and criminal charges and can cause tremendous and irreparable damage to the organization
Examples − Proprietary information, research, and development data protected by state and federal regulations.
Data Classification Process
To classify data to meet compliance standards, the first step is to conduct procedures involving data locations, classification, and determining adequate cybersecurity measures. Each system must be executed depending on your company's compliance standards and infrastructure.
Steps for Data Classification
Step 1: Analyse Risk Assessment
Conduct a risk assessment to determine the sensitivity level of the data. Also, you need to identify security loopholes through which a hacker can breach your network defenses.
Step 2: Develop Classification Policies and Standards
A classification policy and standard can help you streamline the process of adding data in the future to the same category to minimize mistakes.
Step 3: Categorize Your Data
Once you set the classification policies and standards, you need to assign categories to data based on their sensitivity. Also, mention penalties for non-compliance with these policies and standards.
Step 4: Find a Location to Store Data
Make sure to find a safe and secure location for data storage before deploying cybersecurity defenses. Allotting data to their site makes it easier for you to deploy the proper cybersecurity protection.
Step 5: Classify Your Data
You can do it manually or use third-party software to identify and classify data and track them.
Step 6: Employ Controls
Employ controls so that the individual must require authentication to access the data. The person must send authorization access requests to the respective authority and can only access the data if their request is approved. It will be better if an individual is only permitted to access the information if they need it to perform a task in their job.
Step 7: Monitor Data and its Access
Monitoring data is a crucial step for compliance and maintaining privacy. Without regular monitoring, you couldn't know whether there was an unauthorized attempt to access the data. With proper monitoring controls, you can detect loopholes and anomalies in your security system and remain vigilant to eradicate a threat from the network before it could happen.
With accurate data classification, organizations get a crystal-clear picture of all data in the organization's control. It gives a clear understanding of the storage location of the data, ways to access them seamlessly, and the best ways to protect them from unauthorized access. It streamlines your organization's security framework and facilitates top-level data protection measures while promoting employing compliance with the company's data security policies and regulations.
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