What are the three types of information classification according to the IS policy?
Data classification tags data according to its type, sensitivity, and value to the organization if altered, stolen, or destroyed. It helps an organization understand the value of its data, determine whether the data is at risk, and implement controls to mitigate risks. Data classification also helps an organization comply with relevant industry-specific regulatory mandates such as SOX, HIPAA, PCI DSS, and GDPR. Show
Blog: Top Challenges to Implementing Data Privacy: Nailing Down Discovery and Classification First is Key. Data Sensitivity LevelsData is classified according to its sensitivity level—high, medium, or low.
× Jan 19 Upcoming Webinar × Data Sensitivity Best PracticesSince the high, medium, and low labels are somewhat generic, a best practice is to use labels for each sensitivity level that make sense for your organization. Two widely-used models are shown below. If a database, file, or other data resource includes data that can be classified at two different levels, it’s best to classify all the data at the higher level. Solution Spotlight: Enable Data Discovery and Classification. Types of Data ClassificationData classification can be performed based on content, context, or user selections:
Data States and Data FormatTwo additional dimensions of data classifications are:
Blog: How Organizations Manage to Understand Millions of Unstructured Data Files at Scale. Data DiscoveryClassifying data requires knowing the location, volume, and context of data. Most modern businesses store large volumes of data, which may be spread across multiple repositories:
Before you can perform data classification, you must perform accurate and comprehensive data discovery. Automated tools can help discover sensitive data at large scale. See our article on Data Discovery for more information. The Relation Between Data Classification and ComplianceData classification must comply with relevant regulatory and industry-specific mandates, which may require classification of different data attributes. For example, the Cloud Security Alliance (CSA) requires that data and data objects must include data type, jurisdiction of origin and domicile, context, legal constraints, sensitivity, etc. PCI DSS does not require origin or domicile tags. Creating Your Data Classification PolicyA data classification policy defines who is responsible for data classification—typically by defining Program Area Designees (PAD) who are responsible for classifying data for different programs or organizational units. The data classification policy should consider the following questions:
Data classification can be the responsibility of the information creators, subject matter experts, or those responsible for the correctness of the data. The policy also determines the data classification process: how often data classification should take place, for which data, which type of data classification is suitable for different types of data, and what technical means should be used to classify data. The data classification policy is part of the overall information security policy, which specifies how to protect sensitive data. Data Classification ExamplesFollowing are common examples of data that may be classified into each sensitivity level. Sensitivity LevelExamplesHighCredit card numbers (PCI) or other financial account numbers, customer personal data, FISMA protected information, privileged credentials for IT systems, protected health information (HIPAA), Social Security numbers, intellectual property, employee records.MediumSupplier contracts, IT service management information, student education records (FERPA), telecommunication systems information, internal correspondence not including confidential data.LowContent of public websites, press releases, marketing materials, employee directory.See how Imperva Data Security Solutions can help you with data classification. Request demo Learn more Imperva Data Protection SolutionsImperva provides automated data discovery and classification, which reveals the location, volume, and context of data on premises and in the cloud. In addition to data classification, Imperva protects your data wherever it lives—on premises, in the cloud and in hybrid environments. It also provides security and IT teams with full visibility into how the data is being accessed, used, and moved around the organization. What are the 3 types of information classification?Data classification generally includes three categories: Confidential, Internal, and Public data. Limiting your policy to a few simple types will make it easier to classify all of the information your organization holds so you can focus resources on protecting your most critical information.
What are the information classification policies?A data classification policy is a comprehensive plan used to categorize a company's stored information based on its sensitivity level, ensuring proper handling and lowering organizational risk.
What are the three classifications used by the information protection scheme?The simplest scheme is three-level classification:. Public data — Data that can be freely disclosed to the public. ... . Internal data — Data that has low security requirements but is not meant for public disclosure, like marketing research.. Restricted data — Highly sensitive internal data.. How many classifications are there in our information classification policy?Typically, there are four classifications for data: public, internal-only, confidential, and restricted.
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