Data has never been more important. With data breaches on the rise and the complexity of sensitive data growing, organizations are under huge pressure to protect their digital assets. But what happens when even the most advanced DLP tools fail?
This is the story of a major security vendor that changed their DLP strategy with advanced classification and overcame the impossible.
What is DLP?
Data Loss Prevention (DLP) is a key part of modern data security. It’s a set of technologies and processes that protect sensitive data from unauthorized access, use, disclosure, modification or destruction. The aim of DLP is to prevent data breaches and ensure compliance with regulatory requirements by identifying, monitoring and automatically protecting sensitive data across endpoints, networks and cloud.
DLP solutions work by identifying sensitive data such as personal identifiable information (PII), financial records and intellectual property and applying policies to prevent unauthorized access or transfer. By implementing DLP organizations can protect their digital assets, maintain data integrity and protect sensitive data from threats.
Understanding the DLP Challenge
Before we get to the solution let’s look at a real world scenario many organizations face:
A major security vendor already has anti-spam solutions in place and is looking to enhance their proprietary Data Loss Prevention (DLP) product. Their email DLP is fully working but they are still developing their endpoint DLP. However they are struggling with their existing file extraction and classification tools which are not up to the mark. They are also dealing with a large technology vendor and the relationship is complex which is causing delays and uncertainty in their DLP strategy.
This scenario illustrates three key problems:
Incomplete DLP coverage (especially endpoint protection)
Poor file extraction and classification
Vendor dependencies causing delays and strategy uncertainty
These are not unique. Our research shows many organizations are facing similar issues. The search volume for terms like “data loss prevention software” (4,400 monthly searches) and “DLP solution” (4,400 monthly searches) shows there is a big market demand for DLP solutions. So they need to adopt a full data loss prevention solution to enhance their proprietary DLP product.
The Problem: A Stuck DLP Strategy
For years they had been using a proprietary DLP solution. Their email DLP was working well and robust but their endpoint DLP was still in development and they had a big gap in their data protection strategy that could be filled by implementing full DLP policies.
Compounding the problem was their old file extraction and classification tools which were struggling to keep up with modern data environments. And to top it all a long standing relationship with a large technology vendor was going sour and causing delays and uncertainty in their plans.
The pressure was on. Customers were asking for full DLP solution, competitors were ahead and internal teams were stretched thin to fill the gaps. They needed a solution – and they needed it fast.
The Breakthrough: Advanced Classification for Sensitive Data
Enter advanced classification technology, a solution to the modern data protection challenges. Unlike traditional tools advanced classification had the precision, scalability and flexibility the organization needed to take their DLP to the next level.
This wasn’t just a fix for their existing problems; it was a complete rethink of how data could be identified, categorized and protected. It also prevented data transfer by monitoring network traffic and implementing policy controls to protect sensitive data.
With the advanced classification solution they found:
A Foundation for Growth: Pre-built policies in multiple languages gave them a head start in policy enforcement so they didn’t have to start from scratch.
Flexibility at Scale: Seamless integration across both Windows and Mac platforms so their endpoint DLP could finally become a reality.
Easy Deployment: APIs that simplified integration and flexible pricing so they could customize the solution to their needs.
The Result: From Problems to Solution
The deployment was the start of a new chapter for the organization. Within months they were able to fill the gap in their endpoint DLP and have a full solution that worked across their environment.
The advanced classification technology delivered:
Better Accuracy: Machine learning-driven classification reduced errors so sensitive data was identified and protected without downtime.
Faster and More Reliable: Outdated tools gone so workflows were faster.
Resilience to Vendor Issues: By not being tied to a single vendor they could adapt and innovate without external blockers.
But the biggest win was not operational – it was strategic. Their customers now had a full DLP solution that set a new benchmark in the market and cemented the organization’s position as a security leader. The advanced classification technology improved accuracy and efficiency but also protected data at every stage of access, share and storage so data was safe from leaks.
Data Security Threats
In today’s digital world data security threats are evolving and can impact an organization’s data integrity, confidentiality and availability. Common data security threats are cyber attacks, malware, insider risks, accidental exposure, phishing and ransomware. These threats can lead to data breaches, data leaks or unauthorized data transfer which can be catastrophic for an organization’s reputation and financial stability.
Cyber attacks and malware can get into systems, steal sensitive data and disrupt business. Insider risks whether malicious or accidental can result in unauthorized data access or exposure. Phishing attacks trick employees into revealing confidential information and ransomware encrypts data and demands payment to release it. To address these threats you need a full data security strategy with robust DLP solutions to prevent data breaches and protect sensitive data.
The Benefits of Advanced Classification in DLP
Advanced classification is the answer to these challenges and taking DLP to the next level. Here’s why:
1. More Accurate and Contextual
Advanced classification uses machine learning and natural language processing to understand the context and content of the data. This goes beyond simple keyword matching or regular expressions so you can:
Identify sensitive information more accurately
Reduce false positives and save time and resources
Handle unstructured data which is a large proportion of enterprise information
Action: When implementing advanced classification start by defining clear data categories based on your organization’s needs. For example create categories for “Financial Data”, “Personal Identifiable Information (PII)”, “Intellectual Property” and “Confidential Business Information”. This will give you more precise policy enforcement.
2. Scalability and Performance to Prevent Data Breaches
With data growing exponentially scalability is key. Advanced classification solutions are designed to handle large volumes of data so you can:
Classify data in real-time at rest and in motion
Consistent performance across multiple data sources and formats
Ability to scale without performance degradation
Action: When evaluating classification solutions test performance thoroughly. Simulate your expected data volumes and variety to make sure the solution can handle your current and future needs. Look for solutions that offer distributed processing to maintain performance as your data grows.
3. Flexibility and Customization
Every organization has different data protection needs. Advanced classification solutions offer:
Customizable classification rules and policies
Industry-specific terminology and regulations
Easy integration with existing security infrastructure
Action: Develop a data classification policy that reflects your organization’s risk appetite and regulatory requirements. Get stakeholders from different departments (IT, Legal, Compliance, HR) involved in this process to make sure all perspectives are considered.
DLP Solutions and Technologies
DLP solutions and technologies are designed to protect sensitive data from unauthorized access, use, disclosure, modification or destruction. They come in many forms; network DLP, endpoint DLP and cloud DLP each addressing different aspects of data protection.
Network DLP monitors and protects data as it moves across the network, preventing data transfer. Endpoint DLP secures data on endpoint devices such as laptops and mobile devices so sensitive information remains protected even when accessed remotely. Cloud DLP protects data in cloud environments and integrates with cloud access security brokers (CASBs) for full protection.
These DLP solutions use advanced technologies such as encryption, access controls and data loss prevention software to protect sensitive data. They can also be integrated with other security solutions such as endpoint detection and response (EDR) systems to provide a layered defense against data breaches.
Deploying DLP
Deploying a DLP solution requires planning, preparation and deployment. First you need to identify your organization’s sensitive data and classify it based on its sensitivity and business value. This means understanding where sensitive data sits, how it’s used and who has access to it.
Next you need to develop a DLP policy that outlines the procedures and guidelines for protecting sensitive data. This policy should cover all aspects of data protection including data access controls, encryption and incident response.
Once the DLP policy is in place the solution should be deployed across multiple locations; endpoints, networks and cloud environments. This will give full protection to sensitive data wherever it sits or is accessed.
Finally, the organization should monitor and review the DLP solution regularly to make sure it’s preventing data breaches and unauthorized data transfer. This means continuous data monitoring, policy updates and employee training to maintain a robust data protection strategy.
By following these steps you can deploy a DLP solution that protects sensitive data, prevents data breaches and is compliant with data privacy regulations.
Advanced Classification Impact on Data Protection
Advanced classification will make your DLP more effective:
More Accurate: By understanding context advanced classification reduces false positives and negatives so truly sensitive data is protected without hindering productivity.
Full Coverage: With the ability to classify data across multiple platforms and formats you can have consistent protection across your entire data estate.
Compliance: Advanced classification helps you meet regulatory requirements by identifying and protecting sensitive data, reducing the risk of non-compliance fines.
Better User Experience: By reducing false positives and more accurate classifications users are less likely to get frustrated or try to bypass DLP controls.
Future Proof: The flexibility of advanced classification solutions means your DLP can adapt to new data types and emerging threats.
For organizations facing similar challenges the message is clear: innovation is not optional – it’s mandatory. Advanced classification technology gives you the tools to build not just a better DLP solution but a better future for data security.