In 2021, over 22 billion records were exposed in around 4100 data breaches, and 2022 is expected to have exceeded this by 5 percent.
Data breaches put the safety of many people at risk and can cause devastating damage to a business' reputation.
Protecting data from breaches means having a solid system of managing and storing this data which starts with a data classification plan and policy.
In this blog, we'll go over all the need-to-know about data classification policy (DCP) and how to get started creating one for your company and organization.
What is Data Classification?
Simply put, a DCP categorizes information based on how sensitive the content is.
Once a business classifies the data, it can also find out what level of protection and security are required for it. For example, a company will examine digital records and transactions, classify the data into groups, and then set parameters to protect each group. People working in data classification hold positions like data stewards, data managers, or data scientists are the ones who manage this data.
Why Does Your Business Need a DCP?
If you're like most businesses, you have a lot of data. Customer data, financial data, employee data, intellectual property - the list goes on. And with all this data comes the risk of data breaches and leaks. That's why it's so important to have a data classification policy in place.
A data classification policy is a set of guidelines that help you determine how to protect your sensitive data. It helps you label your data so you know which information needs to be kept confidential and which can be shared openly. It also helps you develop processes for handling and storing data so you can keep it safe from unauthorized access.
Data classification can help with:
- Safeguarding business information by maintaining the integrity, availability, and confidentiality of data
- Maintaining compliance with all rules, regulations, and laws
- Identifying who has access to the data and how often
- Determining the duration of data retention for record-keeping purposes and security measures
- Maintaining client trust
- Establishing a culture of data security
- Maintaining the company's reputation and brand
- Saving time, money, and the integrity, availability, and confidentiality of data by concentrating appropriate controls on specific data
What are the five main types of data classification?
With a data classification policy, a company can outline the process of dealing with sensitive data to help prevent or reduce the possibility of hacks and data breaches. There are five common types of data classification, which are:
1. Public data
Public data is important information that is freely available (or is in the public domain). It can be read, researched, reviewed, and stored by anyone. Since it is freely shared and passed around and presents little or no risk if accessed by others, it typically has the lowest level of data classification and security.
Examples of public data: first and last names, company names and founder information; dates of birth or dates of incorporation; job descriptions and position postings; press releases; organizational charts; and license plate numbers.
2. Private data
Private data is information that's kept from the public's view; one's email inbox or smartphone home screen is information you might keep private by using a password or fingerprint access features. Private data sharing, erasure, or modification typically entails a small risk to an organization or person.
Examples of private data: are phone numbers and email addresses; research information or previous online activity; email messages or phone content; and employee identification cards.
3. Internal data
This often relates to a company, business, or organization. Only employees usually have access to official internal data.
Examples of internal data: business plans and strategies; internal emails or memos; company intranet; budget spreadsheets and revenue projections; email and messenger platforms; archived files; URLs; and internet protocol (IP) addresses.
4. Confidential data
Confidential data is in which only a small number of people or parties have access to sensitive information, which requires clearance or special authorization. Access may involve identity and authorization management components, such as restricted file links or password authentication.
Confidential information may or may not be shared within departments of the same company. It is common to restrict who has access to sensitive information, and in some cases, signing a non-disclosure agreement may be necessary to further safeguard confidentiality.
Examples of confidential data: indicators of social security numbers on state-issued identification cards or licenses; vehicle identification numbers; health and medical histories; credit cards numbers, pin codes, and expiration dates; information on the magnetic strip of a credit card; financial statements; employee records; and biometric identifiers like fingerprints.
5. Restricted data
The most delicate category of data is restricted data. The number of people who can access the data is limited by strict security measures; backup systems, such as data encryption, are frequently used to stop malicious users from accessing or reading the content on restricted platforms. Restricted data could endanger public health and safety or a company's or organization's confidential information if it is breached or compromised.
Examples of restricted data: Data protected by confidentiality agreements, information on federal taxes, and private health information (PHI).
Implementing A Data Classification Policy for Your Organization or Company
Classifying data can be a complex task, and there is no one-size-fits-all approach. The best way to develop and implement a data classification plan is to first understand the organization's data and then create a system that makes sense for that data.
Creating groups and categories, along with a document that outlines how data will be classified within an organization, are a few of the first steps. Training employees on the classification process is also an essential part of implementing a data classification policy.
With pre-authored templates that are auditor-approved and employee trainings, 1Fort helps simplify the process. With 1Fort, you can also gain visibility into your endpoints and identify any potential gaps in your coverage by easily integrating your cybersecurity tools.
Sign-up for a free demo and learn how 1Fort can help you and your broker meet this requirement easily.