Just picture this – you are an IT officer of an organization where users create up to millions of emails and documents every day. Such data that drives businesses can be a double-edged sword. If leaked or stolen, organizations face reputational and financial losses. However, some data types need to be accessed by the public in line with business’s objectives.
Companies need to find reliable ways to limit access to confidential data while ensuring public information is freely available for use. Maintaining the security and privacy of an enterprise’s digital information remains a massive task. Fortunately, organizations have found a way to make the work easier by implementing a method that assigns labels to databases, files, records, and other data forms. The process is known as data classification.
What is Data Classification?
Broadly speaking, classification involves organizing data into different categories that help with general usage and efficient protection. In data classification, organizations examine the data they collect, process, share, hold and determine the protection level needed to keep it secure and private. The consistent and repeatable process evaluates digital data, structured and unstructured, and assigns a classification tag based on file types, content, and other metadata.
Purpose of Data Classification
NIST Special Publication 800-60 Volume I Revision 1 indicates that identifying information processed on an information system is essential for the proper selection of security controls and ensuring the confidentiality, integrity, and availability of the system and its data. Classified information is easy to locate and retrieve. The process involves tagging data, making it easily trackable and searchable. Besides, the process eliminates data duplication, effectively reducing storage and backup resource requirements. An official state website in the US clearly defines the purpose of data classification. CT.GOV states that the process establishes protection profiles and assigns control element settings for each category of data for which an agency is responsible.
Based on the capabilities data classification delivers, the process is useful in data security, risk management, and compliance. Information classification provides an operational framework for employees and third-parties involved in collecting, storing, transmitting, or retrieving data. The process helps organizations answer crucial questions about their information and informs how they manage data governance and mitigate risks.
Each file or piece of data is assigned a classification tag in metadata and visible markings, making it easy for data loss prevention solutions to understand data movement and enforce data protection policies accurately.
Why You Should Implement a Data Classification Process and System
Organizations can implement data classification processes to enhance their data security initiatives. In this case, an enterprise classifies data in different categories and implements proper security responses based on the data being retrieved or transmitted. Other than that, an information classification system provides ease of access and improves regulatory compliance. Organizations can easily trach regulated data, optimize search capabilities, discover significant trends inside data, and identify stale information.
In a nutshell, you should implement a data classification process for the following reasons:
- Risk Management: Data classification limits access to confidential and sensitive information, such as personally identifiable data. The process enables organizations to reduce the attack surface area for personal data. With data classification, it is easy to integrate into policy-enforcing applications.
- Compliance and IT Governance: Data classification makes it easy for enterprises to identify data governance by crucial regulations, such as HIPAA, PCI DSS, GDPR, and other data protection laws.
- Optimization: Data classification enables efficient access to information based on type, usage, and other vital factors. Such schemes also eliminate redundant information.
- Analytics: With information classification, organizations can gather insights on location, protection level, and usage of company data.
Data Sensitivity Levels
A data classification strategy creates different sensitivity levels based on the information confidentiality or importance level. The data classification process divides an organization’s data into different categories, ranging from the most confidential (with restricted access) to the least confidential (with no limitations). Data sensitivity levels essentially correlate to the security measures that organizations put in place to protect the levels.
Data classification involves categorizing information into many labels and tags that define the type of data, its integrity, and its confidentiality. Different enterprises use unique terms to refer to sensitivity tiers. Whichever approach a company follows, all stakeholders must know what each data category means, and the method should be consistent.
MyPrivacy proposes dividing information classification into 4 categories:
- High Sensitivity/ Confidential: High sensitivity data can also be described as top secret, company-secrets or restricted information. This classification includes personally identifiable information, such as employee and customer records, financial information, security data, user credentials, and intellectual property (IP). Unauthorized access of confidential data exposes an enterprise to serious legal, reputational, and financial consequences.
- Medium Sensitivity: The second classification type can also be described as sensitive data. The information is meant for company internal use only. It includes data like email and non-confidential business files that employees use daily. Unlike high sensitivity, unauthorized access to medium sensitivity data is not directly catastrophic to the company.
- Low Sensitivity: The third level of classification can be described as data in preparation to be published. All the information necessary to create no-sensitivity data (background information or project details in order to create press releases, sales and/or marketing materials etc.) may not be intended for the public. It may include sensitive information that in the process of creating a final document, needs to be classified with low level sensitivity or partly published with no sensitivity.
- No Sensitivity / Public: No sensitivity data can be described as public or unrestricted information. It includes details that an organization wants to share with or has already released to other stakeholders and the public. Examples of no-sensitivity data include public-facing documents such as press releases, advertising content, sales and marketing materials.
Different organizations usually classify information using other terms. For instance, a post on IT Governance Blog uses confidential, restricted, internal, and public information levels for the model. The article also adds that larger and more complex organizations need more classification categories. With such levels, organizations can effectively devise security rules covering several ways to protect the information, including personal security, physical security, management of the data, information assurance, industrial safety, or the ways organizations share information internally and with third parties.
Data Classification Process
Organizations can follow these steps in classifying information:
- Understanding the current situation: You cannot classify what you do not know. The first step involves determining the data types that an organization collects, transmits, or retrieves. Next, it is vital to identify the data’s location and other factors like required security measures and regulations that pertain to an organization.
- Determine the classification levels: What are the required classification levels, and what controls are needed to protect data in each category?
- Prioritize and classify data: The next step after picturing the current data in an organization involves prioritizing information for classification. An organization should determine the best way to tag data, based on its nature.
- Authentication and authorization: After classifying all the data types, organizations must implement controls to ensure the right people access the correct information and only use specific data in approved ways. Most frequently, enterprises deploy IT security solutions to achieve data authentication and authorization. For instance, employees can use user ID and password to access a system and retrieve confidential and sensitive data. Indeed, both authentication and authorization become more critical as the level of data sensitivity increases.
Repeatedly, the above data classification process can be a complex and cumbersome undertaking. Organizations can, fortunately, leverage automated systems to streamline the process. However, deploying technology in information classification requires companies to determine the classification criteria and define the process’s objectives.
Tips on how to implement a data classification process / system
- Take Business Needs into Consideration: It is essential to develop and implement a data classification method that meets the enterprise’s business needs.
- Align Leadership on Information Classification: Data classification must be done by those who understand an organization’s business needs and data sensitivity in relation to those needs. In this case, the executive must collaborate with internal IT departments to implement a data classification strategy. Business owners handle the classification since they know how the process will impact the business needs.
- Define Owners for Specific Data Type: It is significant to define different owners for specific data—for instance; the human resource manager may own payroll information. Data owners are responsible for the precise classification of the information they hold.
- Frequently Reassess Classification: Organizations should maintain a flexible data classification method that allows occasional information reclassification in relation to business needs. For instance, a business can reclassify internal pricing schedules as public or unrestricted information.
- Automate Data Classification: Data classification solutions allow enterprises to identify information that is crucial to an organizations’ interests. Businesses can blend automated techniques and user-driven data classification procedures to deliver significant benefits such as improved insights generation.
- Communicate to Stakeholders: Involve employees in the data classification process to achieve the right data protection and regulatory compliance.
Data is Not Simple to Classify - How MyPrivacy Can Help
Often, data is not easy to classify. Many organizations face difficulties in implementing and adhering to a formal information classification scheme. Many businesses, including those who commit to protecting sensitive and confidential information, fail to maintain an effective data classification strategy. Others do not have any information classification scheme at all. As a result, businesses remain at risk of severe losses because of the lack of proper data classification procedures.
To create an efficient data classification system, it requires initial efforts, ongoing commitment and discipline. Developing a scheme with sufficient controls needs training of stakeholders to recognize and classify information accordingly. The scheme may also lack the cultural clout required to gain acceptance by all stakeholders.
MyPrivacy provides a modular and flexible data protection system to support governance requirements. We provide customers with the right set of technologies and expertise to prevent unauthorized access or manipulation of their confidential and sensitive data. MyPrivacy solutions enable the secure exchange of classified data from human to human, human to machine, machine to human, and machine to machine.