Data classification is the practice of tagging and organizing data into pre-defined categories, making it easier to locate and retrieve while enforcing secure access for authorized users.

Data classification practices are necessary for maintaining a strong security posture. By ensuring that security teams know where to find sensitive information and by putting rules in place about who is allowed to access it, you can prevent or contain data breaches and keep unauthorized users away from resources they shouldn’t have.

Content-based classification: This is the practice of examining files and searching for sensitive information inside them. This can be helpful if you have a problem of information that is not for public consumption hiding in seemingly innocuous file types.

Context-based classification: Instead of examining file contents directly, this approach primarily looks at the metadata associated with files to find clues indicating that data inside is sensitive. This may include identifying the location where a file is saved, which user created it or which application the file is built for. This approach works well when your user base is well-trained and when you already have a degree of control over your sensitive data.

User-based classification: This puts the burden upon users to comb through files and categorize them. While at its best this approach can significantly cut down on false positives, it relies upon having not only a highly trained user base but also the time to manually classify data. That means that it is typically only suitable for a leaner organization or a smaller dataset..

Identification: Find where your sensitive data resides, including cloud repositories and physical hard drives, and take any necessary immediate steps to secure them with encryption, physical access controls, etc.

Organization: Come up with the process that you will use to organize data into categories.

Training: Empower employees to take a role in tagging data and placing it in the proper place based on its category. The more people who have a role in the process, the more stringent your training needs to be to make sure that human error doesn’t compromise your efforts.

Compliance: Understand the applicable data security and data privacy regulations for your operations, along with the penalties for noncompliance.

Solutions: Locate the data classification solution that best suits your organization. In many cases it can be best to utilize a comprehensive data security platform that can assist with data discovery, classification and prioritization instead of patching together different solutions from various vendors.

Yes, Forcepoint Data Classification can help streamline compliance in 80+ regions. It helps you avoid costly non-compliance fines with out-of-the-box key regulations and the broadest coverage of data types in the industry.

Forcepoint Data Classification uses AI-powered precision and efficiency. It helps classify data across multiple sources, using AI Mesh technology, to continuously improve its accuracy and efficiency, saving organizations valuable time and resources.

Forcepoint Data Classification uses AI Mesh to deliver highly accurate data classification. Its networked AI architecture relies on a Small Language Model and advanced AI components to improve efficiency and reduce false positives.