DLP helps organizations protect their sensitive data. Learn about the best practices and tools available to prepare for and prevent data loss.
Data loss prevention enables organizations to protect their sensitive data. Learn more about best practices and tools available to protect businesses from data loss.
While no organization is completely immune to cyber threats, there are some tools that can help mitigate this risk. One category of such tools is DLP, which is becoming an increasingly common component of an overall data privacy and security strategy.
SEE: Learn how to choose the right DLP software for your organization.
Not only is DLP important to protect data from cyber threats, but it also allows organizations to meet their compliance mandates. A properly designed and implemented DLP also helps organizations meet their auditing requirements. In this article, we highlight how DLP works, the types of DLP, and some best practices to follow.
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Data loss prevention (DLP) is a set of software tools, processes and data security practices that help prevent unauthorized access, misuse or loss of sensitive or critical data. It is also referred to as extrusion prevention or information loss prevention.
Corporations often include DLP in their overall data security strategy. It helps them identify attempts by malicious actors to gain unauthorized access to their systems. A typical data breach costs $4.25 million, and considering the increased risk of cyberattacks, DLP is becoming increasingly popular with companies looking for methods to safeguard their digital data.
DLP is classified into three categories: network DLP, endpoint DLP and cloud DLP. While all three types have the same overall objective of preventing data loss, there are some key differences in the techniques used to achieve this objective.
Network DLP is used to monitor and protect data on the company’s servers. This includes data that is at rest and in motion. Network DLP analyzes data traffic on the cloud and on traditional network systems to identify any violation of a company’s security policies. This type of DLP monitors file uploads and transfers, emails and messaging on the company network. If any user tries to gain authorized access to sensitive information on the company servers, network DLP will initiate predefined steps to prevent the user from accessing the data.
With network DLP, admins can also view who accessed the sensitive data, when it was accessed and whether the data was moved to another location. This increased visibility helps mitigate the risks of data loss on the network.
Endpoint DLP is designed to protect data that is in transit or in motion. It is specifically designed to monitor the endpoints of the network, such as the cloud repositories, computers, cell phones and other devices that are connected to the network. With endpoint DLP, admins can track data stored on endpoints on and off the company network.
While endpoint DLP offers more comprehensive security compared to network DLP, it does require more management. For example, DLP tools must be installed on all devices that need to be protected. The admins also need to ensure the DLP tools are maintained through regular updates.
As the name suggests, cloud DLP offers protection for data in the cloud. It scans and audits data and automatically flags any anomalies that require attention. In addition, cloud DLP maintains a list of authorized cloud devices, applications and users that have been provided with permission to access data.
Cloud DLP also maintains a log to record when data was accessed and who accessed it. Rather than building a perimeter around the network, cloud DLP interfaces with cloud applications to encrypt data.
Data loss prevention solutions work by classifying types of data, either on-premises or in the cloud, into different categories, such as confidential or business critical, and identifying any violations of predefined rules or policies configured into the software. The use of DLP software helps organizations meet their compliance and regulatory requirements, such as GDPR and HIPAA.
It is vital for organizations to identify and classify sensitive data so they know exactly what type of data they have and what is required to protect it. A great tool for identifying and classifying data is to use a data discovery technology that scans data repositories and generates a report on the type of data.
Automation allows users to offload repetitive and recurring tasks. It also helps with a broader DLP implementation across the organization. While manual DLP processes are important in the initial setup to help configure the system according to the specific needs of the organization, automating the processes helps maximize the scale and scope of DLP implementation.
All business-critical data and sensitive information should be encrypted, including data that is at rest and in transit. With data encryption, organizations have an added layer of defense against cyber attacks. This means that even if an intruder gains access, the encryption helps keep data safe. There are various data encryption technologies available, such as Encrypting File System (EFS) and Microsoft BitLocker.
Determine the level of access required by different users in your organization and configure these rules in the DLP tools. The user roles should clearly define the responsibilities of different users, including the role of stakeholders if data loss occurs.
