Endpoint DLP is an additional data loss prevention tool that can help protect your enterprise from losing sensitive data.
What Is Endpoint DLP?
Endpoint data loss prevention extends to endpoint devices that are used to access sensitive, stored data. Endpoint DLP protects data in use, in motion, and at rest.
What Is Data Loss Prevention?
Data loss prevention is the practice of monitoring, detecting, and preventing potential cybersecurity data breaches, including the illegal transmission, exfiltration, and destruction of sensitive data. DLP incorporates a set of tools and practices to ensure vital data isn’t stolen, leaked, misused, lost, or accessed by unauthorized users.
DLP Data Life Cycle Stages
DLP provides complete data visibility in the network, at all stages of its utility and transmission. A comprehensive DLP solution targets data at three stages:
- Data in use: DLP safeguards data while in use by an application or endpoint. It also encompasses protecting data when it’s being accessed, modified, or processed. This is typically done through authentication, authorization, and identity access control.
- Data in motion: Securing the safe transmission of confidential, proprietary, and sensitive data as it passes through networks, including email and other messaging systems. Encryption is the primary mode of protection here.
- Data at rest: Safeguarding data stored in a storage location, computing device, database, or server, including cloud-based systems. Authentication, encryption, and user access controls are used here for protection.
DLP should be an important aspect of the overall security strategy and posture of an organization. A DLP solution can be deployed at the network, endpoint, or on the cloud.
Network DLP vs. Endpoint DLP vs. Cloud DLP
DLP solutions emerged to protect and prevent companies from risking the loss of confidential and proprietary data, either inadvertently, or due to data leakage or insider threats.
Endpoint DLP
As its name implies, endpoint DLP monitors all endpoints. These typically consist of laptops, desktop computers, servers, mobile, and IoT devices. The list includes any device or component on which data resides, data is used, saved, or moved. The role of endpoint DLP is to monitor these devices to ensure data loss, leakage, or misuse doesn’t occur.
Endpoint DLP has grown in importance and prominence with most companies adopting a bring-your-own-device (BYOD) policy with their employees. The implementation and company-wide rollout of endpoint DLP is more challenging due to its scope.
Hence, its deployment can be an intimidating prospect for most organizations. However, there are some effective endpoint DLP solutions that don’t require complicated and time-consuming execution.
To protect sensitive data such as intellectual property, organizations run endpoint discovery scans and execute remediation actions.
Network DLP
These are the most common DLP solutions. Network DLP’s primary role is to provide visibility into the type of data being sent through a network.
Network DLP is efficient and well-rounded at safeguarding data in motion. To do so, it analyzes the network activity and traffic passing through what is mostly a traditional network. So, it monitors the network in order to detect when proprietary, confidential, business-sensitive data is transmitted in violation of company policy.
However, its focus on network communication means that it’s mainly limited to protected data in motion. Moreover, experts point out that network DLP isn’t capable of protecting an organization from the harm that comes from insider threats.
Cloud DLP
This is effectively a subset of the network DLP and is tasked with protecting data on remote cloud systems. This encompasses data residing with cloud providers and software-as-a-service applications such as Microsoft 365 Outlook, Dropbox, Google Drive, Asana, and Jira.
Cloud DLP protects data in the cloud. It primarily does this through scans and audits to determine the presence of sensitive data, subsequently encrypting it before it’s stored in the cloud. It fortifies this by generating a log that records when confidential, cloud-based data is accessed. It also alerts system administrators and IT operators in the event of anomalous activity or the threat of a breach.
Moreover, offices are shifting more than ever to remote workforces or hybrids of this configuration, with tools like Slack and Google Drive.
Are All of These Necessary? Should an Organization Implement all Three?
For comprehensive security, organizations should endeavor to deploy all three DLP types. Used together, each plays a comprehensive role in the overall data security of an organization.
For instance, endpoint DLP offers data visibility beyond an organization’s network. As a result, it’s vital for keeping the data on devices outside the network’s scope safe, which is especially relevant for those that connect remotely. By installing agents at endpoints, endpoint DLP is capable of accessing, scanning for, and ultimately protecting sensitive data.
Network DLP monitors the network, especially for malware activity, suspicious file transfers, or data exfiltration efforts. It also reports on network bandwidth usage to establish a baseline of operations to detect anomalous activity by suspect actors.
As remote staff and in-office employees transfer data back and forth between corporate communications networks and endpoint devices, a comprehensive DLP solution is necessary to add a robust extra layer of data security.
How Does a DLP Solution Work?
The centerpiece of creating a DLP solution is basically two-fold: First, determine if a particular operation is legitimate or possesses a threat to corporate data. Second, take steps to keep the data protected and secure.
This scenario is an example of how DLP solutions work:
- A rule identifies when an incident occurs; for example, when a user attempts to copy data to a USB or removable device.
- The DLP solution prevents the data from being copied.
- The DLP solution generates a report, which triggers an alert notification to an IT security officer.
DLP software is designed to detect misuse and threats through content awareness and contextual analysis.
Content awareness involves analyzing documents to determine if it contains sensitive information. On the other hand, context analysis examines only metadata and properties of a document like its size, format, and header.
Pattern Matching
Context analysis uses pattern matching to determine whether a document’s content contains sensitive data like social security numbers, credit card numbers, or HIPAA information. Once the DLP software detects a matched pattern with confidential data, it proceeds to issue an alert to warn of violations and trigger an incident response.
The analogy often used to explain this is to equate the content to a letter while the context represents the envelope used to send it. So, while content awareness analyzes the content, context encapsulates external factors like header, size, or format which lets us gain intelligence regarding the content of the envelope.
The technical implementation of context analysis often involves the use of regular expressions, also known as regex.
Context-based classification is paramount for protecting intellectual property, whether it is stored in a structured or unstructured form.
DLP Use Cases
Identifying and Preventing Sensitive Data Loss
DLP assists businesses in identifying security incidents such as data breaches and hardening the IT infrastructure to avert the loss of confidential company data such as valuable intellectual property. This also includes applying different levels of trust to different devices, especially portable ones.
DLP offers additional levels of protection for file transfers and sensitive data in motion by ensuring they are automatically encrypted.
Data Discovery, Visibility, and Regulatory Compliance
The sensitivity of data in the modern age means that organizations face a lot of oversight in their handling. Therefore, DLP helps companies to cover a broad range of government standards and requirements.
One of the roles of endpoint DLP is the discovery and classification of proprietary, confidential data for compliance and reporting purposes. In addition to intellectual property information and proprietary data, DLP protects the treatment of personally identifiable information that falls under the auspices of privacy regulations like HIPAA, GDPR, PCI DSS, and so on.
A major part of the regulatory requirements for these agencies is that organizations know where data is stored, especially at endpoints, or run the risk of non-compliance and face deep fines.
Protecting Against Data Leakage at User EndPoints
Endpoints such as laptops and mobile devices are very susceptible to data leakage because they are prone to connecting to unsecured networks. In addition, they are more likely to be stolen, misplaced, or damaged. Due to the massive growth of IoT, endpoints can also provide a conduit through which attackers can gain access to internal networks.
Implementing DLP on endpoints helps monitor access to confidential and sensitive data on those devices.
Best Practices for Endpoint DLP
Adopting best practices helps to fortify your DLP endpoint implementation. Here are a couple of DLP best practice strategies to consider.
Classify Your Data
While modern organizations have increasingly become data-driven, not all data is created equal. Effective DLP starts with data classification, separating, and prioritizing sensitive and nonsensitive data.
Therefore, clearly defining your data is vital for effective DLP and risk management. As a result, DLP should be positioned to protect your organization’s crown jewels, more so than any other category of data.
Define, Monitor, and Report Your Metrics
The only way to ascertain the efficacy of DLP efforts is for companies to establish the key performance indicators (KPIs) they need to measure closely.
Subsequently measuring these target metrics will show whether there are areas for improvement and the positive impact of DLP with regards to its business value to the organization.
This process should also include documenting and reporting DLP policies and processes so there can be institutional knowledge concerning DLP cybersecurity measures.
Design and Implement a DLP Policy
DLP implementation should never follow an ad hoc or scattershot approach.
Even the best DLP software cannot perform effectively in a vacuum. To get the most out of a DLP solution, companies need to outline the rules and procedures that’ll best safeguard their data resources.
Some of these might include using identity access management to track and control the type of information different categories users can see. Others include defining a comprehensive incident response in case of a data breach and adopting mitigation and remediation strategies in the event of a threat.
How Fortra Secure Collaboration Helps You with Endpoint Data Loss Prevention
Fortra has deep expertise in tightening data protection for enterprises with DLP solutions. They provide data visibility and comprehensive protection for all endpoints.
Fortra Secure Collaboration extends DLP security to endpoints, enabling businesses to apply policies that protect, track, manage, and audit them in real-time. Fortra Secure Collaboration also brings much-needed flexibility to DLP with its data-centric approach:
- Relaxes stringent rules with regard to unstructured data, thereby improving user experience.
- Data security policies are enforced wherever and whenever the data is accessed.
- User access can be granted or revoked at any time, thereby building adaptive trust.
- Fortra Secure Collaboration solutions extend an organization’s control down to the data itself.
To learn more about data loss prevention and how to bulletproof your endpoints, read about our DLP solutions here.
