The Relationship between Data Integrity and Security

High-quality data is the primary value proposition of research labs. To protect their bottom line, labs must implement mechanisms to ensure the authenticity and accuracy of their data. Protecting data integrity involves employing systems that secure sensitive information and prevent unauthorized access—objectives that are all accomplished with effective data security practices. By prioritizing the relationship between data integrity and security, labs can uphold product quality, ensure client privacy, and protect their value offering.

The interplay of data security and integrity

Data security and integrity are inherently coupled. Without robust security measures in place, the integrity of data is constantly at risk, subject to manipulation by user error, sabotage by threat actors, and destruction by local disasters. Data security is not a binary state in which a lab is either “secured” or “unsecured”; it is a broad set of protocols that work to minimize risk. Data security is a collection of complementary practices, not a single, one-size-fits-all solution.

In turn, data integrity can aid in data security. With accurate, trustworthy data sets, organizations can identify threats and anomalies more effectively, perform more accurate security audits, and ensure regulatory compliance.

Essential security practices for data integrity

There are a variety of measures that labs can enact to ensure the security, and thereby integrity, of their data. A data security solution should be holistic, covering every aspect of the lab and the unique flows of every data stream. While this list isn’t comprehensive, some fundamental security practices for every lab include data encryption, access control, and regular backups.

• Data encryption: A secure solution will encrypt data both in transit and at rest. When relaying data from the lab to the cloud service provider, the data should be sent only over a secure communication protocol, namely, HTTPS, which is the standard HTTP web protocol wrapped in an encrypted SSL connection. With HTTPS, data intercepted by third parties cannot be read. Data should also be encrypted when in storage in the event that a threat actor gains access to the hardware that the data is stored on. By protecting data with end-to-end encryption, sensitive data stored in an ELN, LIMS, or other program will not be easily compromised by external threat actors.
• User access control: Users should only receive the minimum permissions possible to execute their role, a concept known as least privilege. By practicing least privilege, organizations can minimize attack surface and mitigate errors—malicious insiders will have fewer opportunities to steal or sabotage sensitive data.
• Backups: In the event of a worse-case scenario in which production data is lost or corrupted, data backups allow labs to restore the data and resume operations with minimized downtime. Backups are a core component of overall security.

The relationship between data integrity and security forms the backbone of a lab’s operational excellence and credibility. High-quality data is the lifeblood of research labs, and protecting that data begets the implementation of various security measures. Securing data is not just a necessity, but a strategic imperative, and labs that do that successfully will protect their bottom line and enhance their reputation.