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Enhance regulatory compliance with context-rich data classification

As the collection and use of consumer data by enterprises, agencies, and institutions continues to increase, so do the number of privacy regulations put forth to keep this information safe. These regulations come with strict requirements and hefty penalties, so it’s of the utmost importance that organizations do everything they can to comply.

This is much easier said than done, but the world of data security technology is ever-evolving, too, and its sights are always set on delivering more accurate, more efficient, and more streamlined capabilities. Enter: Context-rich classification, the next generation of data classification. In addition to bolstering data security and governance strategies, it also enhances your organization’s ability to comply with even the strictest of data privacy regulations. This article aims to illustrate how.

What is context-rich data classification?

After sensitive data has been created or discovered within an organization’s environment, it is classified based on its sensitivity or confidentiality level so it can be secured. This is all well and good, but privacy regulations are specific; they want to know why data was collected and how it will be used, when data was collected and when it will be disposed of.

Context-rich classification allows for this granularity, applying metadata tags for details like:

  • Why an organization is collecting that data from an individual;
  • The business process(es) for which the data will be used;
  • What a data subject’s preferences are for their data’s use;
  • All the regulations that would govern that data; and
  • Any custom specifics an organization would like to include, such as data subjects’ locations or third-party processors.

What’s more, with context like this applied to data at the file-level, you strengthen subsequent components of your security ecosystem, like rights management and data loss prevention (DLP) solutions, for example.

Specific ways context-rich classification enhances compliance

Because context-rich classification can tag based on the regulatory standards it’s subject to, your organization will be well-primed to comply with their seemingly endless requirements.

Context-rich data classification for CPRA compliance

The California Privacy Rights Act (CPRA) is a regulation introduced in 2020 that seeks to protect the personal information of California residents and will officially take effect in 2023. It is essentially a more stringent version of its predecessor, the less restrictive CCPA. Some of the CPRA’s new requirements include:

  • A higher level of protection for the new subcategory of sensitive personal information (SPI). This grouping, which merits a higher level of protection, includes Social Security numbers, debit and credit card numbers, driver’s license numbers, SMS and email contents, biometric data, race and ethnicity details, religious beliefs, union membership, and more.
  • The implementation of risk-based controls over user log-in information, such as encrypting usernames and enforcing multi-factor authentication, to proactively avoid data breaches generated from this source.
  • Disclosing the purpose(s) for data collection, as well as its retention period. If the retention period itself cannot be disclosed, then the criteria used to determine retention periods must be.
  • Giving data subjects expanded rights over their data, including the right to correct their information, the right to limit the use and disclosure of their SPI, and the right to request information about automated decision-making and opt out of the process.

With context-rich data classification software, personal information and SPI are labeled with precision so they receive the levels of security they require. In addition, this data can be accurately mapped, so it’s readily accessible to fulfill data subject rights. To comply with CPRA retention requirements, metadata tags identifying purpose of collection and file creation date ensure sensitive information isn’t kept around longer than it should be.

Context-rich data classification for NIST compliance

The National Institute of Standards and Technology’s Special Publication 800-53 applies to all federal agencies and specifies how they should maintain their information systems, including any applications and integrations, with specific security and privacy controls. NIST 800-53 recommends categorizing data as low, moderate, or high based on the level of its impact if it were compromised. When NIST conducts audits, it looks to ensure any data within its jurisdiction is labeled accordingly with the corresponding security measures applied, and context-rich classification makes this possible.

As this data then moves through the rest of its security ecosystem, it’s able to do so in accordance with not only NIST 800-53’s policy requirements, but those of the other regulations it’s governed by. For example, protected health information (PHI) — part of NIST 800-53’s high-impact category — is also regulated by HIPAA, which has its own categorization schema and requirements to comply with. Similarly, financial account information and credit card numbers are highly regulated by both NIST 800-53 and PCI-DSS, but again, each with their own sets of requirements and noncompliance penalties.

Context-rich data classification for CMMC compliance

A Cybersecurity Maturity Model Certification (CMMC) is mandatory for any organization, contractor, or vendor in the defense supply chain. There are multiple certification tiers, but even the lowest level requires a certain number of cybersecurity controls and practices in place to protect CMMC-regulated data, called controlled unclassified information (CUI), and demonstrate basic cyber hygiene. CUI can be financial, legal, or infrastructure data, but because it’s within the confines of the Defense Industrial Base’s network of companies, contractors, and vendors, it must meet CMMC security requirements.

In order to do this, these organizations need a context-rich classification tool in place capable of identifying and labeling CUI as such. This way, CMMC-required controls and security measures can be applied to it. What’s more, CMMC-regulated organizations must be recertified after three years, and they should ideally be seeking the next level of certification each time. With CUI that’s richly contextualized, these organizations can more efficiently fulfill the requirements of the next certification tier, which involves increasing the number of security controls and practices in one’s environment. In short, context-rich data classification helps you fortify your security infrastructure and enables your cyber hygiene to grow more and more sophisticated.

Bolster compliance with context-rich data classification by Spirion

Spirion is the critical first step toward data privacy and security. We build and deliver the most accurate data discovery and classification solutions on the planet to position our customers for unparalleled data privacy, security, and regulatory compliance.

Contact us today to learn how our context-rich, automated data classification capabilities can help your organization meet numerous compliance regulations, including CPRA, NIST, and CMMC.