In today’s digital age, a tidal wave of information travels across networks from user to user and device to device. Organizations rely on collecting and storing sensitive and personal information to perform business-critical operations, such as collecting credit card payments, performing banking transactions and tracking packages.

And, of course, with data collection comes the need for data regulation to protect sensitive and personal data from leakage, theft or misuse. While it is great for customers to know their data is in safe hands, organizations that deal with growing amounts of data often struggle to keep pace with evolving regulations.

The primary categories of protected data are personal data and sensitive data. Though they might sound similar, these data types are categorized differently under regulations, which impacts how they should be protected.

With so many legal terms and regulations in place, individuals and organizations need to stay attuned to the differences between the two types of data to protect the security and privacy of the business and customers. Let’s define these different categories of data and why they are important for data security, privacy and compliance.

What is personal and sensitive data?

Personal data is defined by the General Data Protection Regulation as any information that is “related to an identified or identifiable natural person.” Any information that can identify a person, directly or indirectly, should be considered personal data. This includes name, address, phone number, email address and date of birth, as well as information related to work, education and hobbies.

Sensitive data requires a higher level of protection due to its potential harm if exposed. It includes highly confidential information that, if mishandled, could cause significant damage. This includes data that a malicious actor could use to harm an individual or organization, such as financial information, medical records, passwords and social security numbers. Sensitive data is typically subject to strict privacy and security regulations, and its misuse or exposure can have severe consequences.

There is a lot of personal information available for public access. For example, creating a profile on Facebook that displays your name, home and education is easily accessible from a simple Google search. If a profile is public, the Facebook user has given permission to Facebook and anyone who accesses the page to view their information. But if a user sets their profile to private, Facebook has the responsibility to keep that information viewable to only select users.

Companies such as Facebook must handle users’ personal data with care because it can be easily traced back to an individual, especially when information is grouped together to provide context. Personal data can become sensitive, depending on how it is collected and stored.

Differentiating personal data and sensitive data

Personal data is not always considered sensitive, and sensitive data may not necessarily be personal. Data becomes personal data when it can be connected to a specific individual.

Organizations often collect multiple pieces of personal information from a single user. While one piece of data may not be specific enough to be traced back to the individual, today’s technology can easily connect individual pieces of data together. This means that while personal data is not always considered confidential or sensitive in nature, it should still be protected from being accessed, manipulated or abused.

It is important to differentiate what data is public knowledge and what needs to remain confidential. Even within a company, not all employees are eligible for the same privileges to view sensitive or personal data. Understanding what kinds of data are being accessed, used and distributed is an essential first step towards complying with regulations and protecting customer and business data.

Key differentiators for data security, privacy and compliance

The primary difference between personal and sensitive data is the level of harm that can be caused by its exposure. While a malicious actor can use personal data for spamming, phishing or identity theft, the exposure of sensitive data can lead to serious harm, such as financial loss, medical identity theft or reputational damage.

There is a difference between personal data and sensitive data when it comes to the legal implications surrounding their collection, use and disclosure. Certain laws and regulations explicitly define and protect specific categories of sensitive data. For example, healthcare privacy laws like HIPAA may consider health data to be sensitive data.

Personal data becomes sensitive data when it pertains to specific categories or attributes that require special protection because of the potential effect of a breach on an individual’s privacy, security or fundamental rights. While the distinction between personal data and sensitive data can vary depending on legal frameworks and contexts, there are three common criteria that can trigger the classification of personal data as sensitive:

1. Sensitive categories: Personal data relating to sensitive categories, such as race or ethnicity, religious or philosophical beliefs, political opinions, trade union membership, genetic data, biometric data or health information, is generally regarded as sensitive.
2. Contextual sensitivity: Personal data can also be considered sensitive based on the context in which it is used or disclosed. Information that, if exposed or misused, may cause harm, discrimination, stigmatization or significant impact on an individual’s rights may be deemed sensitive.
3. Potential for harm: If personal data has the potential to cause substantial harm, such as financial fraud, identity theft or reputational damage, it may be considered sensitive due to the risks involved.

Put the right protections in place

Organizations need to put the right measures in place to keep their business and customer data safe. While personal data is relatively common and may not be confidential depending on the industry, sensitive data is subject to strict regulation.

As such, organizations that collect and store sensitive data must take appropriate measures to protect it from unauthorized access or misuse. This includes implementing data encryption and access controls and regularly monitoring and auditing systems to ensure compliance with data protection regulations.

As organizational data expands across hybrid environments, it becomes increasingly difficult to determine what data is personal vs. sensitive, who should have access to it and how to monitor it. Organizations dealing with vast amounts of sensitive data must have granular access controls and protective measures in place to maintain security, privacy and compliance without sacrificing efficiency and increasing costs.

The IBM Security Discover and Classify solution helps organizations understand their data and how to protect it by automatically scanning and continuously cataloging the data, whether it is personal data, sensitive data or both. It classifies the data and supplies business context around it so users can know why and how it needs to be protected. By using AI-driven technology to classify data, IBM’s solution ensures that organizations are aware of the different types of data they are collecting and that they are handling it properly. Having precise context for data is incredibly useful when it comes to monitoring the data landscape for both security and compliance purposes.

Personal data vs. sensitive data: The bottom line

The bottom line is that sensitive data differs from personal data in that it encompasses information that, if exposed, could cause significant harm, violate privacy or result in potential legal and financial consequences. While personal data provides a broader understanding of an individual’s identity, sensitive data requires heightened protection due to the potential impact of its mishandling or disclosure.

Organizations must employ robust data security measures such as encryption, access controls and continuous monitoring to ensure the proper handling and protection of sensitive data for security and compliance purposes.

By prioritizing the security and privacy of sensitive data, organizations can demonstrate their commitment to protecting individual information, fostering trust with their clients and keeping business processes in compliance with regulations.