DLP

Data Loss Prevention

Data loss prevention (also known as DLP, data loss protection, data leak prevention, information loss prevention, or extrusion prevention) is a strategy for seeking to prevent sensitive or critical information from being extracted from your corporate network. The term is also used to describe software products that help a network administrator control what data can be transferred outside your corporate network.

 Understanding DLP Solution         

A DLP solution depends on a number of key technologies that enable its engine to correctly identify the sensitive data that enterprises need to secure and adopt remediation action to prevent incidents.

Today, DLP solutions employ different technologies. DLP technologies are broadly classified into two categories: Enterprise DLP and Integrated DLP.

  • Enterprise DLP: These solutions are comprehensive and packaged in agent software for servers and desktops, virtual and physical appliances for monitoring networks and email traffic, or soft appliances for data discovery.

 

  • Integrated DLP: These solutions are limited to secure email gateways (SEGs), secure web gateways (SWGs), enterprise content management (ECM) platforms, data classification tools, data discovery tools, email encryption products, and cloud access security brokers (CASBs).

There are multiple content analysis techniques which can be used to activate policy violations, including:

Rule-Based/Regular Expressions: The most common analysis technique employed in DLP involves an engine’s analyzing content for particular rules such as 9-digit US social security numbers, 16-digit credit card numbers, etc. This technique is considered to be an exceptional first-pass filter since the rules can be configured and processed swiftly, even though they can be prone to high false positive rates without checksum validation to detect valid patterns.

Conceptual/Lexicon: Using a combination of rules, dictionaries, etc., these policies are capable of alerting on completely unstructured ideas that challenge simple categorization. It will have to be customized for the DLP solution provided.

Statistical Analysis: Employs machine learning or other statistical methods such as Bayesian analysis to activate policy violations in secure content.

Pre-built categories: Pre-built categories with dictionaries and rules for common types of sensitive data, such as HIPAA, credit card numbers/PCI protection, etc.

Database Fingerprinting: This technique is also known as Exact Data Matching. It looks at exact matches from a database dump or live database. This is an option for structured data from databases even though database dumps or live database connections affect performance.

 

Why Organizations Need Data Loss Prevention?

 Business organizations go through major financial losses and reputational damage when they experience loss of sensitive data and other forms of enterprise information. Companies are now very much aware of these dangers and hence data protection has become the most trending topic, however many organizations fail to completely understand the business case for Data Loss Prevention  (DLP) initiatives. Some of the major effects of Data loss/leak on the organisation are as follows:    

  • Loss of reputation
  • Loss of intellectual property
  • Compromise of corporate security
  • Violation of statutes and compliance requirements
  • Harmful legal judgments

 

What Does DLP Provide

Given below are some of the key reasons why an organization needs DLP:

  • DLP technology provides IT and security staff with a 360-degree view of the flow, location, and usage of data across the enterprise. It is capable of checking network actions against an organization’s security policies, and also enables you to protect and control sensitive data, including personally identifiable information (PII), financial data, customer information, and intellectual property.
  • When used along with complementary controls, DLP enables preventing the accidental exposure of personal information across all devices. Wherever data lives, DLP has the potential to monitor it and majorly reduce the risk of data loss.
  • Technology controls are becoming essential to attain compliance in specific areas. DLP provides these controls, including policy templates and maps that automate compliance, address particular requirements, and enable the collection and reporting of metrics.
  • DLP provides updated policy templates and maps that address specific requirements, help in the collection and reporting of metrics, and automate compliance. After a policy need is detected, DLP can make the modification as simple as helping a suitable policy template on your system.
  • When organizations fail to adopt the necessary steps to detect sensitive data and protect it from misuse or loss, they are actually risking their potential to compete. Companies that obtain data protection and privacy right can boost their brand reputation and resilience going forward. However, those that get it wrong are likely to end up in financial loss and reputational damage. DLP thus enables protecting critical data and preventing negative publicity and loss of revenue that certainly follow data breaches.