Expanded Definition: Data Loss Prevention
What is data loss prevention?
Data loss prevention (DLP) is a category of practices and products that aim to minimize the negative impacts of a network breach by monitoring and managing the data that can be accessed by both authorized and unauthorized users.
For example, if an employee tries to share a document containing private user data with a contractor that does not have authorized access to this information, a DLP tool could be used to alert the employee of this error or even block them from sharing the information.
Another example may be if the contractor who should have not access to a document containing sensitive information is able to access the data and attempts to send it out of the organization.
DLP solutions protect organizations against insider threats while also ensuring that they remain compliant with data privacy regulations. The average cost of a data breach reached $3.92 million in 2020, and in a post-pandemic landscape factors such as cloud app sprawl and the shift to a larger work-from-anywhere workforce have only heightened security concerns. The number of endpoints and third-party applications within organizations’ networks have increased, which gives DLP tools more ground to cover.
Once information has been inventoried, it can then be classified with a DLP management framework. The product can be used to classify three types of data:
- Data in Use: Stored in RAM or actively being processed by a CPU
- Data in Motion: Being sent between devices both inside and outside of a network
- Data at Rest: Not actively being sent between devices and stored physically in computer data storage
A variety of DLP techniques are then used to protect sensitive data from exfiltration, using content and context awareness to monitor the proper use of the data by authorized users.
The MSP role in Data Loss Prevention
With many customers’ network security under their purview, managed service providers (MSPs) rely upon DLP solutions to help catalog and monitor their data while preventing and detecting any data loss. Traditionally, these solutions have required heavy lifting in the setup and deployment phases, however advancements in machine learning for content and context awareness is making enterprise DLP solutions a better fit for MSPs.
Additionally, data visibility is highly important to MSPs. Innovations in monitoring and response technologies used within DLP solutions are offering more agile, granular views into the status of data within the network and the root causes of endpoint device threats. To reduce the increased overhead burden, the DLP alerts may be sent to the SIEM to be correlated into the rest of the security events to provide a better picture.
As most DLP solutions offer policy protections for common data compliance standards like HIPAA, GPR, CCPA and more, these tools also improve your clients’ security posture in the face of ongoing regulations.
Maintaining a Data Inventory
Knowing where organizations’ sensitive data is stored and processed is the first step in stopping bad actors, curbing the harm of employee mistakes, or preventing catastrophic data loss. This data inventory must include a wide variety of sources such as:
- Network Devices
- End-user Devices
- Storage Area Networks
- Backup Arrays
- File Shares
- Third-Party Applications and Cloud Applications
While data discovery is the first step of the inventory, a DLP solution must also be able to classify the data in order to protect it. For example, you need to ensure that your tool is addressing protected health information (PHI) and board meeting notes differently.
Providing Data Backup and Recovery
While DLP solutions help prevent data breaches, having a backup plan when incidents do occur helps MSPs lessen their impact. In the immediate aftermath of a security incident, every second counts. Establishing a data backup and recovery plan allows MSPs to provide both peace of mind in the “what-if” scenarios and a fast response in the face of disaster.
Did you know?
18.1% of documents uploaded to file-sharing services contain sensitive information, such as personally identifiable information , protected health information, payment card data, or intellectual property, thus creating compliance concerns.
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