Types of DLP (Data Loss Prevention)

TL;DR

• Data Loss Prevention (DLP) is a security solution to protect sensitive or confidential data from unauthorized access, use, disclosure, transfer, or destruction.
• DLP software can be implemented in various forms, such as network-based, endpoint-based, or cloud-based, to cover multiple data channels and sources.
• Cloud DLP solutions offer several advantages over traditional DLP solutions in terms of reducing false positives and negatives.
• Cloud DLP solutions are essential for any organization storing sensitive data in the cloud or on SaaS apps.
• Strac is a Cloud DLP solution that automatically detects and redacts (masks) sensitive data from all Cloud and SaaS apps.

Understanding Data Loss Prevention (DLP) and Its Role in Cybersecurity

Data Loss Prevention (DLP) is a security solution to protect sensitive or confidential data from unauthorized access, use, disclosure, transfer, or destruction. It is typically achieved through technology and policy enforcement, aiming to identify, monitor, and block sensitive data from being transmitted or stored insecurely. DLP solutions can be implemented in various forms, such as network-based, endpoint-based, or cloud-based, to cover multiple data channels and sources.

How DLP Software Works

DLP software works by continuously identifying, monitoring, and protecting sensitive data across an organization’s SaaS applications, endpoints, cloud storage, and communication channels. Modern DLP goes beyond simple pattern matching; it understands context, evaluates data flows, and automatically enforces security policies in real time. As businesses adopt more SaaS tools and AI-driven workflows, DLP software becomes the centralized control system that detects risks at the moment they occur and takes action to prevent unauthorized exposure.

DLP tools typically operate through three core functions; data discovery, monitoring, and policy enforcement. Data discovery scans all environments for PII, PHI, PCI, secrets, and regulated data. Monitoring analyzes where the data travels and who interacts with it. Policy enforcement executes automated actions such as redaction, masking, blocking, alerting, labeling, or quarantining. Combined, these capabilities ensure that sensitive data is continuously protected across every surface where it appears.

Modern DLP platforms like Strac simplify this even further by using agentless integrations, ML/OCR detection, and real-time remediation to ensure businesses secure their data without slowing down workflows.

✨Types of DLP

1.How Network -Based DLP

Network-based Data Loss Prevention (DLP) is a DLP solution that monitors and controls the flow of sensitive data over a network. This type of solution is implemented at the network layer and monitors all incoming and outgoing network traffic to identify and block the transmission of sensitive data.

Network-based DLP solutions work by inspecting network traffic and comparing it to predefined policies and rules defining what constitutes sensitive data. If sensitive data is detected, the solution can take action to block the transmission, quarantine the data, or send an alert to the appropriate personnel.

This type of DLP solution can provide comprehensive protection for sensitive data transmitted over a network, including email, file transfers, and web traffic. Additionally, it can be integrated with other security technologies, such as firewalls, intrusion detection systems, and anti-virus solutions, to provide a more comprehensive security posture.

However, network-based DLP solutions can also be complex to implement and maintain, as they require deep understanding of network protocols and traffic flow and knowledge of the specific sensitive data that needs to be protected. They also require proper configuration of the network architecture and devices to support the DLP system's monitoring capabilities, and ongoing management of the system's performance and accuracy.

In summary, network-based DLP solutions offer comprehensive protection for sensitive data transmitted over a network but can also be complex to implement and maintain. It is important to assess the organization's specific security needs and resources before choosing a DLP solution.

2. Endpoint-Based DLP Works to Protect Data

Endpoint-based Data Loss Prevention (DLP) is a type of DLP solution that monitors and controls the use of sensitive data on endpoints, such as desktops, laptops, and mobile devices. This type of solution typically involves installing software on each device that monitors the user's actions and enforces policies designed to prevent the unauthorized transfer or storage of sensitive data.

Endpoint-based DLP solutions can monitor a wide range of activities, including file transfers, email, instant messaging, and the use of cloud storage services. If sensitive data is detected, the solution can take action to block the transmission, quarantine the data, or send an alert to the appropriate personnel.

This type of DLP solution can protect sensitive data even when it is stored or transmitted outside of the network, such as when a user takes their laptop off-site or uses a personal device for work-related activities. Additionally, endpoint-based DLP solutions can provide detailed information about the use of sensitive data, such as who is accessing it, when, and from where.

However, endpoint-based DLP solutions can also be seen as intrusive and restrictive by users, as they closely monitor their device usage and can restrict their ability to use certain applications or transfer certain files. Additionally, if the DLP solution generates a high number of false positives, it can erode user trust and lead to users attempting to bypass the solution.

In summary, endpoint-based DLP solutions protect sensitive data stored or transmitted on endpoints, but can also be viewed as intrusive and restrictive by users. It is important to assess the organization's specific security needs, resources, and user acceptance before choosing a DLP solution.

3. Cloud-Based DLP: The Future of Data Loss Prevention

Cloud Data Loss Prevention (Cloud DLP) is a service that uses machine learning to automatically discover, classify, and protect sensitive information like Personally Identifiable Information (PII), financial data, and other types of confidential data. This data could be located in data storage systems, databases, and file systems within both cloud-based and on-premise environments.

Cloud DLP is designed to protect data in the cloud, ensuring that confidential information is not lost, misused, or accessed without authorization. It offers features such as automated data discovery, data de-identification (like masking, redaction, and tokenization), and risk analysis.

Cloud DLP is a subset of the broader DLP (Data Loss Prevention) concept. The traditional DLP focuses on protecting sensitive data within an organization's network or its endpoints (like workstations and mobile devices).

Strac protects all SaaS apps like email, slack, zendesk, salesforce, box, jira, intercom and more.

The Shortcomings of Traditional DLP Solutions and How Cloud DLP Addresses Them

There can be several reasons why a Data Loss Prevention (DLP) solution may fail:

1. Insufficient coverage: DLP solutions may not be able to monitor all data channels or endpoints, leading to gaps in protection.
2. False positives: DLP systems may flag legitimate data as sensitive and block it, leading to business disruption and reducing trust in the solution.
3. False negatives: DLP systems may not identify all instances of sensitive data, allowing it to be transmitted or stored in an insecure manner.
4. Complexity: DLP solutions can be complex to implement and maintain, requiring specialized knowledge and resources, leading to misconfigurations and ineffective protection.
5. User resistance: DLP solutions may be seen as intrusive and restrictive, leading to users bypassing or disabling the solution, undermining its effectiveness.
6. Evolving threats: New data leak vectors and methods of exploitation may emerge, rendering DLP solutions outdated and ineffective.

In summary, DLP solutions can fail due to technical limitations, lack of user adoption, and the constantly evolving threat landscape. It is essential to regularly assess and update DLP strategies to ensure that sensitive data remains protected.

Learn More about Network DLP vs Cloud DLP vs Endpoint DLP

Benefits of DLP Software

DLP software provides organizations with end-to-end control over the security and compliance of sensitive information across SaaS, cloud, endpoints, and communication channels. As companies handle increasing amounts of regulated data, DLP tools reduce exposure, identify vulnerabilities, and enforce consistent policies across every system. This unified approach helps teams maintain compliance with frameworks like GDPR, HIPAA, SOC 2, and PCI DSS.

The key benefits of adopting DLP software include stronger data visibility, improved compliance posture, and automated protection that minimizes human error. By reducing manual oversight and centralizing security controls, DLP tools lower operational risk and help security teams move faster and more confidently.

Core Benefits

• Continuous visibility into sensitive data; organizations know exactly where PII, PHI, PCI, and confidential information reside across SaaS tools and devices.
• Automated protection and policy enforcement; DLP prevents data leakage with real-time actions such as redaction, blocking, labeling, and alerting.
• Reduced false positives through ML/OCR detection; modern DLP avoids noisy, regex-only detection and instead understands context for higher accuracy.
• Compliance readiness and audit support; built-in templates and remediation workflows help organizations meet strict regulatory requirements.
• Lower deployment and maintenance effort; agentless, cloud-native platforms like Strac integrate quickly with minimal engineering overhead.

DLP software ultimately helps teams scale securely by preventing accidental or unauthorized exposure while maintaining the productivity of internal users and external-facing systems.

✨5 Reasons Why Cloud DLP is the Superior Choice for Data Protection

Cloud Data Loss Prevention (Cloud DLP) systems offer several advantages over traditional DLP solutions in terms of reducing false positives and negatives. These benefits stem primarily from the advanced technologies used in Cloud DLP systems, including machine learning, big data analytics, and natural language processing.

Here's how Cloud DLP helps improve accuracy:

1. Machine Learning and Artificial Intelligence: Many Cloud DLP solutions leverage machine learning and AI to improve the accuracy of data classification and detection of potential data leaks. These technologies enable the system to learn from previous instances and improve its accuracy over time, thereby reducing false positives and negatives. Cloud DLP solutions can perform advanced real-time analysis of large amounts of data. They can analyze complex patterns and correlations, leading to more accurate detection of potential data leaks and reducing false alarms.

2. Customizable Policies: Cloud DLP solutions often offer more flexible and customizable policies than traditional DLP solutions. This allows businesses to fine-tune the DLP system according to their specific needs and risk tolerance, which can help minimize false positives and negatives.

3. Integration with Cloud Services and SaaS apps: Since Cloud DLP solutions are designed specifically for the cloud, they can more deeply integrate with cloud services and understand their specific data handling and sharing patterns. This can lead to more accurate data leak detection and fewer false alarms compared to traditional DLP solutions.

4. Contextual Analysis: Cloud DLP solutions are often better equipped to perform contextual analysis of data, meaning they can understand the context in which data is being used or shared. This can help the system differentiate between legitimate and potentially harmful data usage, reducing false positives and negatives.

5. Continuous Learning and Improvement: Cloud DLP providers frequently update their algorithms based on new data and threat patterns. This continuous learning process allows Cloud DLP solutions to keep pace with evolving threats and improve their accuracy over time.

However, while Cloud DLP solutions generally offer advantages in terms of accuracy, it's important to note that the performance can vary depending on the specific solution and how well it's been configured and tuned. No DLP solution can guarantee 100% accuracy, so choosing a solution that best fits the organization's specific needs and risk tolerance is important.

Why Your Business Needs a Cloud DLP Solution: Benefits and Advantages

Cloud Data Loss Prevention (Cloud DLP) solutions are essential for any organization storing sensitive data in the cloud or on SaaS apps. They offer several benefits that make them a valuable investment:

1. Regulatory Compliance: Various industries are governed by strict data protection regulations, such as GDPR, HIPAA, PCI-DSS, and others. Failure to comply can lead to severe fines and reputational damage. Cloud DLP solutions help organizations automatically discover, monitor, and protect the sensitive data that falls under these regulations, thereby ensuring compliance.
2. Data Visibility: As organizations move more data to the cloud or on SaaS apps, it can become challenging to maintain visibility over sensitive information. Cloud DLP solutions offer automated data discovery capabilities that can identify and classify sensitive data across various cloud services, providing a better understanding of what data you have and where it's located.
3. Reduced Risk of Data Breaches: Data breaches can have substantial financial and reputational impacts. By implementing a Cloud DLP solution, businesses can significantly reduce the risk of unauthorized access or loss of sensitive data.
4. Scalability and Flexibility: Cloud DLP solutions are more scalable and flexible compared to traditional on-premise DLP systems. They can be easily expanded or contracted based on business needs and usually provide a range of customizable features to match unique business requirements.
5. Cost-Effectiveness: Since a third-party provider hosts Cloud DLP services, businesses save on the costs of hardware, maintenance, and personnel that would be needed for an on-premise solution.
6. Real-Time Protection: Cloud DLP solutions can provide real-time data protection, instantly flagging potential risks and preventing data leakage as it occurs.
7. Protection for Remote Work: With the rise of remote work, sensitive data is accessed from many locations, increasing the risk of data loss. Cloud DLP can help protect sensitive information, regardless of where it's accessed.

In conclusion, investing in a Cloud DLP solution ultimately comes down to the organization's specific needs. Factors to consider include the type and sensitivity of data, regulatory requirements, the complexity of the cloud environment, and the potential cost and impacts of a data breach.

✨Introducing Strac DLP: A Comprehensive Cloud-Based Data Loss Prevention Solution

Strac is a Cloud Data Loss Prevention (DLP) solution that automatically detects and redacts (masks) sensitive data (images, text, audio, video) from all Cloud and SaaS apps (email, slack, zendesk, intercom, AWS services, Google Drive, One Drive, ChatGPT, and more).

Strac's machine learning software is highly accurate, pre-trained over millions of documents, comments, chats, audios and videos. You can choose from a huge catalog of sensitive data elements. Get configured list for HIPAA, PCI, SOC 2. Create custom data elements that are important to protect for your company. Join our Slack community and try it for free.

Strac also exposes redaction (masking), detection APIs that you can integrate with your apps.

Strac Zendesk DLP Redaction Demo

Bottom Line

Data Loss Prevention is no longer optional; it is foundational to modern cybersecurity. As sensitive data spreads across SaaS tools, cloud platforms, AI workflows, endpoints, and internal communication channels, organizations need DLP solutions that provide real-time visibility and automated protection. Traditional tools that only alert are no longer enough; businesses require systems that detect, remediate, and enforce security policies instantly. Platforms like Strac offer a unified, agentless approach that reduces risk, improves compliance, and protects sensitive information everywhere it moves. DLP is ultimately what ensures companies stay secure, compliant, and resilient in a fast-evolving threat landscape.

🌶️Spicy FAQs on Types of DLP (Data Loss Prevention)

What is Data Loss Prevention (DLP) and why is it important for cybersecurity?

Data Loss Prevention (DLP) is a cybersecurity strategy and technology stack designed to identify, monitor, and protect sensitive information from unauthorized access, exposure, or exfiltration. As organizations increasingly rely on distributed systems and cloud applications, DLP becomes essential for preventing data breaches caused by human error, insider threats, or malicious attacks.

DLP is important because it:

• Ensures sensitive data such as PII, PHI, PCI, secrets, and financial records stays protected;
• Helps organizations maintain compliance with regulations like GDPR, HIPAA, SOC 2, and PCI DSS;
• Reduces the risk of data leakage across SaaS tools, endpoints, and cloud systems;
• Prevents costly breaches that can lead to financial penalties and reputational damage.

How does Network-Based DLP protect sensitive data?

Network-Based DLP monitors and controls data movement across an organization’s network perimeter. It inspects traffic flowing through firewalls, VPNs, email gateways, and web proxies to spot sensitive information leaving the environment. If a policy violation is detected, the system automatically blocks, alerts, or quarantines the transfer.

This type of DLP protects sensitive data by:

• Analyzing traffic in real time to detect unauthorized transmissions;
• Scanning outbound emails, uploads, and messages for regulated data;
• Enforcing security policies before data leaves the organization;
• Providing audits and logs to help security teams investigate incidents.

Network-Based DLP is especially useful for organizations with hybrid or on-premises networks that need centralized visibility over data flows.

What are the benefits of using Endpoint-Based DLP in an organization?

Endpoint-Based DLP protects data directly on user devices such as laptops, desktops, and mobile devices. This is critical because many data leaks originate from local actions like copying files, transferring data to USB drives, or taking screenshots.

Key benefits include:

• Protection at the source; data stays secure even when devices operate offline.
• Control over risky actions; such as blocking clipboard use, downloads, file transfers, and external storage.
• Greater visibility into user behavior; allowing security teams to detect insider threats early.
• Reduced shadow IT risk; by monitoring how employees handle sensitive data across unsanctioned applications.
• Stronger compliance posture; particularly in regulated industries with strict device-level controls.

Endpoint-Based DLP gives organizations a granular layer of defense where most interactions with data occur.

Why is Cloud-Based DLP considered the future of data protection?

Cloud-Based DLP is increasingly seen as the future because organizations now store the majority of their sensitive data in SaaS platforms, cloud storage, collaboration tools, and AI systems. Traditional network and endpoint solutions cannot fully protect data that never touches the corporate network or local device.

Cloud-Based DLP leads the future of protection because it:

• Secures data directly inside SaaS apps like Slack, Google Workspace, Salesforce, Notion, and others;
• Monitors files, chats, uploads, and AI prompts where data is actually created and shared;
• Requires no agents or hardware, making deployment fast and scalable;
• Meets the needs of remote and hybrid teams who rely entirely on cloud tools;
• Supports real-time remediation for modern data flows, not just detection.

As cloud adoption accelerates, Cloud-Based DLP becomes the only practical way to ensure comprehensive, end-to-end protection.

How can Strac DLP improve data security for businesses?

Strac strengthens data security by combining DSPM + DLP into a single, agentless platform that discovers, classifies, monitors, and remediates sensitive data across SaaS, cloud, endpoints, and AI workflows. Unlike legacy DLP tools that only send alerts, Strac takes real-time action to reduce risk instantly.

Strac improves security by providing:

• Agentless deployment; fast activation across Slack, Google Workspace, Salesforce, Zendesk, Notion, and more.
• Real-time redaction, blocking, masking, and labeling; preventing exposure the moment sensitive data appears.
• ML/OCR detection; delivering high-accuracy classification across text, files, screenshots, PDFs, and images.
• AI-workflow protection; ensuring sensitive data isn’t accidentally shared with LLMs or AI tools.
• Built-in compliance frameworks; including GDPR, HIPAA, PCI DSS, SOC 2, and more.
• Unified visibility across the entire data estate; eliminating blind spots across SaaS, cloud, and endpoints.

Strac ultimately helps organizations secure their most sensitive information without slowing down their teams; delivering modern DLP designed for modern workflows.