By Prasanna Peshkar
Data Loss Prevention (DLP) embodies an array of methods and instruments committed to preserving crucial data such as personally identifiable information (PII), financial details, proprietary intellectual property, or other significant business-specific information within an organization’s network. Establishing a well-rounded DLP framework is indispensable for any enterprise striving to avert exposure and probable leakage of sensitive data. This article provides a detailed breakdown of the elements that shape a holistic DLP system.
In most businesses, data is dispersed across a range of places – on-site, in cloud storage, or on individual devices. A robust DLP plan’s first course of action is to discover and categorize this data based on its confidential nature. Organizations can efficiently identify and safeguard precious or sensitive data by doing so.
To protect sensitive data, a company needs to identify its whereabouts first. This could include customer credit card information stored on their local network database, employee PII in a cloud-based HR platform, and intellectual property on employees’ personal devices. A DLP system will scan these places, identify sensitive data based on predetermined parameters (like data that fits the pattern of a credit card number), and categorize it accordingly.
Understanding Data Context
The context in which data is used is crucial in determining its sensitive nature. The contextual analysis takes into account who created the data, its frequency of use, who utilizes it, and its contents.
Let’s look at an Excel file with employee contact details to emphasise the significance of context. If the file was generated by the HR department for official use and regularly accessed by authorized individuals, it may be deemed low risk. However, if the same file was created by an unidentified user and accessed infrequently, it might be regarded as suspicious. The DLP system can differentiate these situations through contextual analysis and take appropriate measures.
Creation and Enforcement of Policies
Upon data categorization and context understanding, setting guidelines for handling the identified data is necessary. These policies determine permissible actions with sensitive data, such as who can access it and where it can be shared. Policies must be flexible enough to accommodate diverse scenarios within the organization.
After data categorization and context comprehension, the next step is policy creation. For example, a company could formulate a policy that only HR staff can access PII and it cannot be transmitted outside the organization via email. The DLP system ensures these rules are adhered to and prevents unauthorized actions.
Policy Violation Alerts
A complete DLP system should have a strong alert system in place to flag when a policy has been violated. This alert system should give in-depth information about the violation’s nature, including the implicated data, the individual involved, and the action undertaken.
For instance, with good intentions, an employee decides to email a file with customer PII to their personal email to work on over the weekend. Regardless of their innocent motive, this action contravenes data security policies. The DLP system identifies this breach and sends an alert to the security team, enabling them to act accordingly. “Data loss prevention (DLP) comes with an advanced cloud-based solution that combines traditional endpoint data loss prevention with insider threat protection.”
Encrypting sensitive data, both when it’s at rest and during transit, is a fundamental component of data security. A complete DLP system ensures that encrypted data is indecipherable to unauthorized users.
Encryption is the technique of making data incomprehensible to unauthorized parties. For instance, a DLP system could automatically encrypt all files containing intellectual property when not in use and decrypt them when an authorised individual accesses them. These files would be encrypted again during network transmission to prevent interception.
Enforcing Access Control
Stringent access control measures are pivotal in data protection. Access should be granted strictly on the basis of least privilege (PoLP), meaning individuals only have access to the data and resources they need for their specific roles.
Access control is about ensuring that only authorized individuals have access to certain data. For example, the DLP system could enforce a rule that only finance department employees can access sensitive financial data stored in a particular network folder.
The ability to generate detailed reports of policy breaches or attempted breaches is essential for organizations. These reports help gauge the incident’s extent, facilitate audits, and assist in compliance reporting.
When a policy breach occurs, like a user trying to print a document containing PII from an unsecured printer, the DLP system logs the event and creates an incident report. This report would detail the user’s identity, the document they were attempting to print, and the timing and location of the incident.
A robust DLP system should offer remediation capabilities to address incidents. This could include blocking sensitive data from leaving the network, prompting users for justification or additional authentication, or even remotely erasing data from lost or stolen devices.
The DLP system can execute automated actions to manage incidents. For example, if it identifies sensitive data being transferred to an unauthorized device, it can halt the transfer, ask the user for a reason, or even automatically delete the data if the device is reported as lost or stolen.
System Integration and Compatibility
Integration with Other Systems
For a DLP system to be truly effective, it must seamlessly interface with other systems such as identity and access management (IAM) systems, security information and event management (SIEM) systems, and enterprise mobility management (EMM) solutions.
The integration allows the DLP system to operate in tandem with other security measures. For instance, the DLP system could work with an Identity and Access Management (IAM) system to ensure that only authorized users access sensitive data based on their roles and permissions.
A robust DLP system should be compatible with various platforms, operating systems, and devices, ensuring data protection irrespective of location.
Cross-platform compatibility ensures the DLP system can protect data no matter where it is or what device it’s on. For instance, it could secure data on a Windows desktop, a Linux server, or an Android mobile device, thus providing comprehensive coverage across the organization.
In a time when data is deemed one of the most precious assets, the significance of a robust DLP system is undeniable. Organizations need to deploy a strong DLP system to safeguard their sensitive data and meet various data protection regulations. By integrating data discovery, policy management, data protection, incident response, and system integration, a complete DLP system offers a holistic solution to prevent data loss and alleviate potential risks.