Regardless of the number of clients you have, your business consistently curates data, including that which you generate and collect. In the pre-cloud era of computing, DLP meant you had a locked file cabinet or secure database locked down behind restrictive rights policies.
These days, organizations utilize cloud ecosystems where their sensitive information and mission-critical data reside. Implementing a DLP solution is the most effective way to keep these vastly spread-out data volumes safe.
Let’s dive deep and shed light on the question: What is DLP?
What Is Data Loss Prevention?
Data is the lifeblood behind all processes in the data-driven corporate ecosystems utilized by industry leaders and entrepreneurs. This concept of organizational data includes data from all sources—personally identifiable information (PII) of employees, clients, shareholders, and business partners. Data also refers to project plans, product prototypes, and even extremely sensitive information, such as financial and market strategies.
Data needs to be kept from the wrong hands at any cost. In an enterprise, data protection does not always refer to protecting data from threat actors. Internal threat actors may also have sanctioned access to sensitive data because their roles justify it.
The key questions organizations ask include:
- How do I protect and preserve the integrity of my data?
- How do I keep this data from reaching a person or entity not privileged to the information?
DLP addresses this critical requirement. DLP tools govern data access within an organization’s SaaS ecosystem, allowing access when necessary and concealing information when clear segregation is required. Based on business rules and policies, files can be tracked, limiting the modification and transfer of sensitive information throughout the organization. Whether access or replication of the data is intentional, negligent, or malicious, DLP aims to highlight possible insider risks.
Industry Best Practices for Data Loss Prevention Tools
When organizations invest in a DLP solution, it is often not a turnkey solution that can be successfully implemented and run without any organizational foundation. Organizations need to plan by considering the best practices below.
Apart from planning and deciding to implement a DLP solution, organizations must prioritize their data into clear levels. Since all the curated data should be prioritized as something other than critical, organizations must draw the line in the sand and highlight which information would be the most disruptive when uncovered or leaked. The DLP process should start with the information that is of critical priority.
Furthermore, all data, documents, and information need to be categorized into classifications. These classifications range from public consumption data to confidential or top secret. These classifications will allow the DLP solution to place files and data into context, allowing accurate tracking.
Organizations should also clearly understand the possible risks associated with the availability of information shared across their business. Data is at its most insecure at business endpoints. These endpoints need to be identified and categorized in terms of their safety. An example of a high-risk endpoint is when an employee is allowed to attach a network file to an email.
Communication of corporate DLP policies being enacted is crucial, too. Employees and division managers need to understand with certainty why risky data practices will not be sanctioned.
While implementing a DLP tool, training may be required to educate all employees about insider risks and that DLP is the entire organization’s responsibility, not only the IT or security teams. Employees should be made aware and often reminded of the DLP policies that are in place.
With the adoption of cloud computing and hybrid work, each employee’s endpoint has evolved into an attack surface. Protecting many disparate nodes from data breaches has become incredibly challenging for organizations. Understanding how your data is utilized throughout your organizational SaaS is critical. Monitoring data movements with a DLP solution allows your organization to shed light on its attack surface, highlighting what is happening to sensitive data.