What is Data Loss Prevention?
Data Loss Prevention (DLP) is a comprehensive approach that combines technology, policies, and processes to safeguard sensitive data from unauthorised access, disclosure, use, modification or destruction. DLP solutions help organisations comply with data privacy regulations and minimise the risk of data breaches.
Benefits of DLP
- Enhanced data security: DLP helps organisations identify, classify and protect sensitive data wherever it resides – on devices, in transit or at rest. This minimises the risk of unauthorised access or accidental data leaks.
- Regulatory compliance: DLP assists organisations in meeting various data privacy regulations like GDPR (General Data Protection Regulation) by ensuring proper controls are in place to safeguard sensitive data.
- Improved incident response: DLP solutions can help detect and respond to potential data loss incidents more effectively. By identifying suspicious activity, organisations can take swift action to contain threats and minimise damage.
- Reduced risk of data breaches: DLP plays a crucial role in preventing data breaches by proactively identifying and mitigating potential risks associated with data movement and access.
Use Cases
- Protecting Personally Identifiable Information (PII): DLP can be used to identify and protect sensitive PII data like Social Security numbers, credit card details and passport information.
- Safeguarding intellectual property: Organisations can leverage DLP to protect confidential business information like trade secrets, product designs and marketing strategies.
- Enforcing data governance policies: DLP helps enforce data governance policies by restricting unauthorised data transfers, copying or sharing according to organisational guidelines.
- Complying with industry regulations: DLP solutions can be instrumental in meeting compliance requirements set forth by various data privacy regulations across different industries.
Key Components of DLP
- Data classification: Identifying and classifying sensitive data based on its type (e.g., PII, financial data) and applying appropriate security controls.
- Data discovery: DLP tools scan devices, networks, and cloud storage locations to locate and identify sensitive data.
- Policy management: Defining and enforcing DLP policies that dictate how users can access, transfer, and share sensitive data.
- Content inspection: DLP solutions inspect data content for sensitive information as it’s being transferred or accessed, and can trigger alerts or block actions if violations occur.
- Encryption: DLP can encrypt sensitive data at rest and in transit to add an extra layer of security.
Microsoft and DLP
Microsoft offers several solutions that contribute to a robust DLP strategy:
- Microsoft purview data loss prevention: This cloud-based DLP solution helps organisations identify, classify, monitor, and protect sensitive data across Microsoft 365 services, on-premises locations, and even endpoints.
- Microsoft Azure Information Protection (AIP): Azure AIP allows organisations to classify and label sensitive data across documents, emails and other file types. This classification can then be integrated with DLP policies for enforcement.
- Microsoft Defender for Endpoint: This endpoint security platform includes features that can help prevent data exfiltration attempts from devices.
