Key Takeaways
- Data at rest is stored in locations such as databases, endpoints, file shares, backups, and cloud repositories.
- Data in transit is moving between users, applications, devices, or systems through email, APIs, web traffic, or file transfers.
- Neither state is inherently more secure. Risk depends on the sensitivity of the data, how exposed it is, and which controls are in place.
- Encryption protects data confidentiality, but it does not prevent every type of data loss or unauthorized access.
- Effective protection combines encryption with data discovery, classification, least-privilege access, data loss prevention, and continuous monitoring.
Data in Transit vs. Data at Rest: What the Difference?
Data can move through dozens of systems during its lifecycle. It may be stored in a database, shared through email, uploaded to a cloud application, transferred to a business partner, or downloaded to an employee’s device. At each stage, sensitive information can be exposed if the appropriate security controls are not in place.
Understanding the difference between data at rest and data in transit can help organizations identify these risks and apply the right protections.
Data at rest is information stored on a device, server, database, backup system, or cloud platform. Data in transit is information moving between users, applications, systems, or locations. While encryption is essential for protecting both states, organizations also need data discovery, classification, access controls, monitoring, and policy enforcement to protect sensitive information throughout its lifecycle.
What Is Data at Rest?
Data at rest is digital information that is stored and not actively moving between systems or locations. It may reside on a physical device, an on-premises system, or a cloud-based platform.
Examples of data at rest include:
- Files stored on laptops, desktops, or mobile devices
- Information held in databases
- Documents saved to file servers or network drives
- Data stored in cloud repositories
- Archived email
- System and database backups
- Records stored in SaaS applications
- Data saved to removable media
Data at rest can include customer information, employee records, financial data, intellectual property, credentials, source code, and other sensitive or regulated information.
What Is Data in Transit?
Data in transit is digital information moving between users, devices, applications, networks, or locations. It is also commonly called data in motion.
Examples of data in transit include:
- An email traveling between sender and recipient
- A file uploaded to a cloud application
- Information submitted through an online form
- Data transferred through an API
- Files shared with a third-party vendor
- Web traffic moving between a browser and a website
- Data synchronized between cloud services
- Information sent through a managed file transfer system
- A document downloaded from a collaboration platform
Modern business environments depend on frequent data movement. Sensitive information may travel across endpoints, email, browsers, SaaS platforms, cloud infrastructure, APIs, and third-party systems, often without the security team directly initiating or observing the transfer.
The Role of Encryption in Data Protection in Transit and at Rest
Securing Data Both in Motion and in Storage
Unprotected data, whether in transit or at rest, leaves enterprises vulnerable to attack, but there are effective security measures that offer robust data protection across endpoints and networks to protect data in both states. As mentioned above, one of the most effective data protection methods for both data in transit and data at rest is data encryption.
In addition to encryption, best practices for robust data protection for data in transit and data at rest include:
- Implement robust network security controls to help protect data in transit. Network security solutions like firewalls and network access control will help secure the networks used to transmit data against malware attacks or intrusions.
- Don’t rely on reactive security to protect your valuable company data. Instead, use proactive security measures that identify at-risk data and implement effective data protection for data in transit and at rest.
- Choose data protection solutions with policies that enable user prompting, blocking, or automatic encryption for sensitive data in transit, such as when files are attached to an email message or moved to cloud storage, removable drives, or transferred elsewhere.
- Create policies for systematically categorizing and classifying all company data, no matter where it resides, in order to ensure that the appropriate data protection measures are applied while data remains at rest and triggered when data classified as at-risk is accessed, used, or transferred.
Finally, if you utilize a public, private, or hybrid cloud provider for storing data or applications, carefully evaluate cloud vendors based on the security measures they offer, but don’t rely on the cloud service to secure your data. Who has access to your data, how is it encrypted, and how often your data is backed up are all imperative questions to ask.
Although data in transit and data at rest present different risk profiles, the level of risk ultimately depends on the sensitivity and value of the data itself. Attackers will target valuable information in whatever state — at rest, in transit, or actively in use — is easiest to exploit. For this reason, a proactive security strategy that includes data classification and categorization, along with content-, user-, and context-aware security controls, provides the most effective protection for sensitive data across all states.
Protect Sensitive Data Wherever It Goes
Protecting data requires more than encrypting files or securing network connections. Organizations need to understand what sensitive information they possess, where it is stored, who can access it, and how it moves between endpoints, cloud services, email, applications, and third parties.
By combining data discovery, classification, encryption, least-privilege access, DLP, secure transfer methods, and continuous monitoring, security teams can apply appropriate protection to data at rest and data in transit.
See how Fortra helps organizations discover, classify, and protect sensitive data from endpoint to cloud.
Frequently Asked Questions
5 Steps To Effective Data Protection
Learn the five steps to implementing effective data protection within your organization, and detail how data classification can enhance previously implemented tools, such as data loss prevention tools (DLP), data discovery tools, data governance tools, and more.
