Debbie Most, if not all, businesses store personal information that could be abused if breached. This data includes PII, PHI and PCI.
DLP helps prevent these breaches by identifying and monitoring data movements exceeding policy. This can be done using exact file matching, statistical analysis, and machine learning techniques.
Prevent Unauthorized Access to Sensitive Data
In addition to preventing unauthorized access, DLP monitors data movement and protects PII (personally identifiable information). PII refers to any information that can identify an individual, including names, addresses, phone numbers, email addresses, login IDs, biometrics, geolocation data, and credit card or other payment details. DLP solutions can help protect this information by monitoring employee activity and preventing unauthorized data distribution.
Organizations must define which data is critical and how much damage would occur if lost or stolen, then prioritize the information. Depending on the priority, the DLP solution can set up rules to detect and stop data distribution.
Educating employees is another key component of DLP. Providing education and training in best practices for handling data can improve employee awareness and compliance with recommended DLP policies. This can be done through classes, online training, periodic emails or videos, and even penalties for breaches. DLP solutions can also encrypt data at rest and in transit, adding another layer of security. This helps prevent unauthorized access by malicious actors and prevents data loss from hardware failure, software errors or other environmental factors.
Eliminate the Risk of Data Loss
One of the most serious threats to a business is when data goes missing, whether stolen by a hacker or accidentally lost by an employee. DLP programs can help eliminate the risk of data loss by monitoring for and detecting sensitive information in all types of files, including emails, web searches and cloud file sharing.
Some DLP solutions also protect data in transit by monitoring the movement of information between endpoints, storage systems and other devices. This helps to prevent unauthorized transfers of sensitive information from inside the organization to partners, customers or suppliers.
DLP can be based on rules created by IT professionals or can use machine learning, statistical analysis or other techniques to detect patterns associated with sensitive data. This allows the system to recognize when a particular string of characters represents PII, credit card numbers or additional confidential information that needs protection. Modern DLP solutions let users create custom rules to identify unique data types. This approach can reduce false positives and make the DLP program more useful.
Ensure Compliance
With remote work environments and the increased reliance on cloud-based systems, DLP can help organizations comply with security policies. Whether through specific guidelines and controls for secure remote access technologies, data encryption on personal devices or file-sharing practices, DLP can ensure that the organization follows best practices.
DLP can also monitor data in motion, protecting sensitive information when moved between endpoints or shared with customers, partners and other external parties. This may include securing information when it’s being sent from a corporate network to a remote user device, as well as tracking and monitoring the behavior of users during their interaction with sensitive data.
To ensure DLP’s effectiveness, employees must be made aware of it and the importance of their role in keeping the business safe. This includes educating and training them to understand what constitutes a breach and the financial impact of data loss. A DLP program should also involve management, as DLP policies are only useful with enforcement at the organizational level. Finally, it’s essential to establish metrics for measuring success and sharing reporting with leadership.
Ensure Data Integrity
DLP ensures that only the most important information is saved, allowing you to protect the integrity of sensitive data. This can be accomplished in several ways. For example, some DLP solutions can scan and catalog files based on their metadata or use partial document match and statistical analysis to identify suspicious information. Many modern DLP solutions also allow customers to build and add rules to the solution.
This allows organizations to set priorities for what types of data to monitor and control egress from the network. Implementing DLP technologies on a cloud deployment architecture is also possible, giving you visibility into data at rest and in motion.
Clearly defining the business value of DLP helps your organization gain buy-in from key stakeholders. This is especially important when trying to secure the budget for DLP. It’s critical to weigh the costs and risks against DLP’s regulatory, compliance and intellectual property benefits. This can help you make a more informed decision about which DLP cyber security solution to invest in.
Reduce Costs
DLP can reduce costs by ensuring sensitive data does not end up in the hands of unauthorized parties. For example, it can protect against misconfiguration that led to the massive breach of Equifax or the RSA hack that exposed 40 million employee records. It can also prevent sensitive data from being distributed unintentionally by employees.
Creating a DLP program typically requires an inventory of the organization’s data and where it is stored. This is usually done with a data scanning tool, and the results are used to create DLP policies.
Classification of data is another important step. DLP tools use pre-configured taxonomies or allow you to customize categories like personally identifiable information, financial data, regulated data and intellectual property.
Most organizations start with a pilot DLP program to determine the best security controls and then gradually build the system over time. This approach is less expensive than trying to protect everything in the beginning, and it enables business leaders to get involved in defining success metrics and reporting that can be shared with the rest of the organization.
