Guide: Data Classification Show
Data Classification: Compliance, Concepts, and 4 Best Practices
What is Data Classification?he term data classification refers to processes and tools designed to organize data into categories. The purpose is to make data easier to store, manage, and secure. Data classification systems support organizations in many efforts, including risk management, compliance, and legal discovery. Additionally, data classification systems can improve the usability and accessibility of data, helping organizations derive more value from their information assets. Data classification can improve all three fundamental aspects of information security:
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Why Is Data Classification Important?Data classification provides an interface for organizations to implement controls and procedures across data formats, structures and storage technologies. Classified data allows an organization to define and implement a single policy for handling sensitive data
across multiple systems and data objects. Defining multiple policies per each type of data object is not realistic in today’s data abundant environments.
What Are the Four Data Classification Levels?There are typically four data classification levels in information security:
What Are the Different Types of Classification of Data?While data is classified based on each individual business’s needs, there are a few types of data classification that are more common:
Challenges of Data ClassificationWhile data classification is essential for carrying out various functions, information security is mainly concerned with sensitive data. In most organizations, sensitive data is classified into various sensitivity levels and then mapped to different categories of sensitive data (e.x. personal information). The challenges organizations usually face when classifying data are:
How Do Compliance Standards Impact Data Classification?Many regulations and compliance standards require organizations to perform data classification. Requirements may be different in each compliance standard, depending on the type of data each organization uses, processes, collects, transmits, and stores. Here are several common compliance standards and their data classification requirements:
Data Classification LevelsData sensitivity levels help determine how each type of classified data should be handled. The Center for Internet Security (CIS), for example, recommends three information classes:
The US government has a more extensive classification, with seven levels of data sensitivity:
Using more than three levels can introduce complexities and make data classification hard to control and maintain. Using less than three levels, on the other hand, is considered too simplistic and may lead to insufficient protection and privacy. This is why the majority of organizations use three levels of classification, as advised by the CIS. Here is a generalized form of the CIS classification definitions which you can use in your data classification efforts:
Learn more in our detailed guide to data classification levels Establishing a Data Classification PolicyA data classification policy defines how your organization manages its information lifecycle. The goal is to ensure sensitive information is handled in a manner relevant to the level of risk it poses. A data classification policy should address access and authorization, taking into account the data structure and its day-to-day business uses. Here are several key aspects your policy should cover:
Learn more in our detailed guide to data classification policy 4 Data Classification Best PracticesHere are a few best practices that can help you improve data classification in your organization. Conduct a Data Risk AssessmentA data risk assessment can help you achieve a comprehensive understanding of all data requirements, including those related to company policies and compliance regulations. You should also determine contractual privacy and confidentiality requirements. Define data classification objectives in coordination with all stakeholders—including IT, security, and legal teams. Create a Data InventoryBefore you can classify data, you need to locate it using data discovery techniques and tools. Once you have located all sensitive data, you need to identify and classify it to ensure each type of data is appropriately protected. To make the process efficient and accurate, you can label each sensitive data asset. This can significantly improve your data classification policy enforcement process. You can label data manually or automatically. Intelligent classification systems can automate this process. For example, a data classification system can use predefined policies to automatically identify and classify data, and then tag it with the appropriate classification label. These systems can continuously monitor data, ensuring that it is always classified properly across the entire data lifecycle. Establish Data Security ControlsEach data classification level requires a different level of security. To ensure each level is appropriately protected, you should establish standard security measures. Then, define policy-based controls for each classification label. When defining security measures, you should take into account where each data type resides and the value this data provides to the organization. You can then assess the risks and implement the appropriate controls. Maintenance and MonitoringData is dynamic and requires ongoing monitoring and maintenance. It can be frequently copied, created, modified, deleted, and moved. Since data may undergo many changes throughout its lifecycle, data classification can quickly turn into a time consuming effort. An important way to reduce data classification efforts is to identify which data really needs to be protected, and focus efforts there. Automated classification systems are another way to reduce workloads and ensure fast detection and treatment of newly created sensitive data. Finally, ensure your data classification policies are flexible enough to deal with changes to data structure, new data types, and growing data volumes. Learn more in our detailed guide to data classification best practices Data Classification with SatoriWhat are the 4 types of data classification?Four data classifications are used by the university: Controlled Unclassified Information, Restricted, Controlled and Public. The Data Trustee is ultimately responsible for deciding how to classify their data (see Roles and Responsibilities for list of Data Trustees and additional information).
What are the classification of data?Data classification is the process of analyzing structured or unstructured data and organizing it into categories based on file type, contents, and other metadata. Data classification helps organizations answer important questions about their data that inform how they mitigate risk and manage data governance policies.
What are 3 main types of data classifications?Here are the three most common ways vendors organize the initial data before deciding how it should be classified.. Content-based classification. ... . Context-based classification. ... . User-based classification.. What are the 4 types of data classification Class 11?Name the types of classification of data :. A. Geographical classification.. B. Chronological classification.. C. Quantitative classification.. D. Geometrical Classification.. |