Data Loss Prevention (DLP)

Data Loss Prevention (DLP) is a critical security measure that protects an organisation’s data from unauthorised access and loss. The term often refers to software solutions designed to ensure that data remains under organisational control.

DLP plays a key role in data protection by automatically classifying data using artificial intelligence, machine learning, and pattern recognition. This enables the analysis of both structured data (such as databases) and unstructured data (such as documents and files). The system identifies the type of data being handled, assesses its sensitivity, and enforces policies to ensure proper data management.

When a DLP system detects sensitive data, it can also identify security policy violations or signs of a data breach. This includes attempts to share confidential files outside the organisation, unauthorised access to or modification of sensitive data, and malicious activities such as malware infections or unauthorised device access.

If a violation is detected, the DLP system can immediately respond by blocking unauthorised access, preventing the sharing of critical files, or taking other necessary measures to mitigate potential damage.

For many organisations, DLP is closely linked to regulatory compliance, such as GDPR, which imposes strict requirements on how data must be processed and protected. Modern IT infrastructures can complicate secure data management, as data is often stored both on-premises and across multiple cloud services. Additionally, data is frequently processed across different jurisdictions, making data protection even more challenging.

Implementing Data Loss Prevention (DLP)

An effective DLP strategy begins with identifying and classifying the data your organisation processes. This includes personal data, sensitive information, and business-critical data, as well as mapping where and how this data is stored and used.

Based on this analysis, clear policies must be established on how data should be handled and protected. Your DLP system should then be configured to enforce these rules. It is also essential that employees understand these policies and their importance, as they directly impact daily data-handling practices.

Data Discovery and Classification

The first step is to identify and classify data, such as personal information, financial records, or patent data, depending on how your organisation processes information.

This can be done automatically using data discovery technology or through a manual review process. Proper data classification is crucial for implementing effective security measures to protect organisational data.

Policies and Rules

Once data is identified and classified, rules must be established for access and sharing, both internally and externally. Modern DLP systems monitor activities across networks, devices, and cloud services and can block unauthorised sharing or alert users in real time.

Three Types of Data Loss Prevention Solutions

DLP solutions are typically implemented across the following areas:

• Network-based solutions: Monitor and secure data transmitted over the network.

• Endpoint solutions: Protect computers, smartphones, and other devices from data loss.

• Cloud-based solutions: Monitor and protect data stored or processed in cloud environments.

Threat Scenarios

Data Loss Prevention protects organisations from both internal and external threats. These threats range from accidental errors, where employees unintentionally share confidential information, to targeted cyberattacks aimed at stealing or compromising data.

The table below outlines examples of threat scenarios and how a DLP system can mitigate these risks.

Risk Reduction

This security measure can significantly reduce the risk of data loss, provided the necessary resources are available for proper implementation. With continuous monitoring of the organisation’s data processing and real-time enforcement of data protection policies, an organisation is better equipped to safeguard confidential data and minimise negative consequences, such as financial losses and reputational damage

Information Assets and Processes

Data Loss Prevention can protect an organisation’s information assets and support data processing within key business processes, including:

• Databases: Monitoring for unauthorised queries or data transfers.

• Files: Identifying and protecting confidential documents, whether stored locally or in cloud services.

• Applications: Integrating with business applications to monitor how data is processed and used.

• Emails: Scanning both incoming and outgoing emails to prevent unauthorised sharing of sensitive data.

• Cloud Services: Monitoring and controlling data transfers to and from cloud environments.

Business Processes

Business processes are protected by ensuring that data is handled according to its classification, including:

• Customer Data: Protecting personal information, such as names and addresses, from unauthorised access or leaks.

• Financial Transactions: Ensuring the confidentiality of accounting records and banking details.

• Product Development: Preventing unauthorised sharing of design specifications, research findings, or other confidential information.

• HR Data: Safeguarding employee payroll details and other sensitive personal information from misuse.

Implementation Requirements

Costs

The cost of implementing a DLP system varies depending on the complexity of the organisation’s setup, the number of employees, and the volume of data that needs protection. In general, implementation requires an investment in software, licences, and potentially consultancy services to properly configure the system.

There are also ongoing costs related to maintenance, updates, and employee training. However, with various pricing options available, organisations can typically find a solution that fits their specific needs and budget.

Resource Requirements

To implement DLP effectively, a combination of resources is required, involving:

• IT Experts: Personnel with experience in configuring and managing DLP systems, which may include both internal staff and external consultants.

• Software and Tools: Investment in the appropriate software and related security tools.

• Training: Employees must be trained to use the new systems effectively to maximise the return on investment.

• Documentation: All implemented processes and policies must be properly documented.

Ongoing Maintenance

To maintain effectiveness, a DLP system requires regular updates, audits, and continuous employee training. It is crucial to assign a dedicated team or a responsible individual to oversee the daily operation and maintenance of the system.

Automation vs. Manual Processes

Once the DLP system is configured, it should operate largely automatically, detecting and blocking suspicious activity in real time. However, ongoing adjustments will be required, and in certain situations, manual reviews may be necessary to make informed decisions on data handling.

Data Loss Prevention Software

There are many DLP software providers, but two well-recognised solutions are Microsoft Purview and Forcepoint DLP.

Microsoft Purview integrates seamlessly with Microsoft’s ecosystem, including Microsoft 365. This makes it particularly attractive for businesses already using Microsoft products, as it ensures that DLP functions effectively alongside existing applications.

Forcepoint DLP offers a customisable solution tailored to specific business needs and can be used for network, cloud, and endpoint security.

Related Security Measures

Below are examples of related security measures that complement DLP:

• Access Control

• Encryption

• Logging

• Training and Awareness

• Incident Response Planning

• Data Classification and Handling

• Network Segmentation

• Endpoint Security

• Phishing and Email Security