What is sensitive data, how do you define it and how to protect it
A report revealed that in 2021, sensitive data was the most common target in data breaches. For example, 65% of all sensitive data incidents involve social security numbers (SSN), and 41% of incidents to personal health information because they are valuable targets.
Moreover, most data breaches occur due to third-party or supply chain vulnerabilities, while 25% of sensitive data incidents occur through supply chain weaknesses.
This indicates that valuable data is a prime target for cybercriminals and exploiting the organisation’s third-party supply chain to get this data.
To prevent devastating breaches, organisations have to identify where data is kept safe and exercise effective means for securing it.
Why is identifying sensitive information important?
For many organisations, defining sensitive data and keeping it safe is a complex task because most businesses deal with a wide range of data types that are sensitive in nature.
For example, businesses collect a wide range of information ranging from personally identifiable information (PII) to proprietary knowledge. While both are types of sensitive data, the latter needs to be available to a wide range of users when they need it, while the former should be locked behind security measures.
Moreover, critical laws regarding data security draw fine lines on the type of data organisations use and how they should secure it. For example, the GDPR sets a clear distinction between directly identifiable information and pseudonymous data.
The GDPR states that personal data is information that covers all forms of personally identifiable information (PII) an individual, such as a phone number, complete name, social security number, and license number.
Meanwhile, pseudonymous data refers to non-directly identifying information that does not identify a user directly but provides sufficient context for specific behaviours. The GDPR makes this distinction to encourage organisations to use pseudonymous data over personal information because of the lower risk to individuals.
How to define sensitive data
There are three different levels of personal information that require different layers of security, also known as confidentiality, integrity, and availability.
- Confidentiality: Implement data privacy through measures ranging from cybersecurity software to awareness training.
- Integrity: Maintain consistency, accuracy, and trustworthiness of data throughout its lifecycle.
- Availability: Ensure that all information systems and data are available when needed.
To define sensitive data consistently, a more detailed data classification method is required.
One method that could prove highly effective is confidentiality, integrity, and availability, also known as the CIA triad—a model to guide information security policies within an organisation and help them categorise data appropriately for relevant security measures.
CIA is a foundational principle in cybersecurity because the framework helps organisations accurately categorise and define the sensitivity of their data and assign relevant security measures.
Effective security measures to protect sensitive data
There is a wide range of data security techniques that include:
- Data encryption
- Two-factor authentication
- Soft tokens
- Key fobs
- File permissions
- Version control
- Cryptographic checksums
- Backups
- Redundancies
Moreover, there are several data security processes organisations should implement to protect sensitive data. These include:
- Implementing safeguards against data loss
- Scheduling hardware maintenance and repairs
- Patching software regularly
- Offering sufficient communication bandwidth
Protecting sensitive data requires you to weave these techniques and processes into an effective cybersecurity framework that would keep your data safe.
Moreover, since most cyber breaches were done by external actors entering the supply chain, devising effective measures for measuring vendor security could be critical. With organisations working with hundreds of vendors, their attack surface is much larger than before, providing many entry points for cybercriminals to enter and obtain sensitive data.
To prevent this from happening, organisations need to take extra measures to better monitor the supply chain, such as vendor risk rating solutions and attack surface management platforms.
Furthermore, a sensitive data catalogue provides insight into sensitive data by providing detailed information on security and privacy and additional metadata, such as the purpose of processing and security controls.
A data catalogue can provide organisations with a snapshot of the data type, its key attributes, and who has access to it. This would improve security and monitoring.
Keeping information safe in the cloud
As regulatory bodies pass stringent laws, defining and securing sensitive data becomes more critical than ever before. A data breach not only represents a significant monetary cost for most organisations but a severe cyber breach of compliance violations.
To prevent these problems, devising a quantitative method for defining sensitive data and devising robust and impenetrable security measures to protect data from data breaches in the future is vital.