Data in transit, or data in motion, is data actively moving from one location to another such as across the internet or through a private network. Data protection in transit is the protection of this data while it’s traveling from network to network or being transferred from a local storage device to a cloud storage device – wherever data is moving, effective data protection measures for in transit data are critical as data is often considered less secure while in motion.
Data at rest is data that is not actively moving from device to device or network to network such as data stored on a hard drive, laptop, flash drive, or archived/stored in some other way. Data protection at rest aims to secure inactive data stored on any device or network. While data at rest is sometimes considered to be less vulnerable than data in transit, attackers often find data at rest a more valuable target than data in motion. The risk profile for data in transit or data at rest depends on the security measures that are in place to secure data in either state.
Protecting sensitive data both in transit and at rest is imperative for modern enterprises as attackers find increasingly innovative ways to compromise systems and steal data.
The Role of Encryption in Data Protection in Transit and at Rest
Data can be exposed to risks both in transit and at rest and requires protection in both states. As such, there are multiple different approaches to protecting data in transit and at rest. Encryption plays a major role in data protection and is a popular tool for securing data both in transit and at rest. For protecting data in transit, enterprises often choose to encrypt sensitive data prior to moving and/or use encrypted connections (HTTPS, SSL, TLS, FTPS, etc.) to protect the contents of data in transit. For protecting data at rest, enterprises can simply encrypt sensitive files prior to storing them and/or choose to encrypt the storage drive itself.
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.
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.
