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Source: Constantin Stanciu via Alamy Stock Photo
Data loss prevention (DLP) is an information security strategy that helps organizations prevent data breaches and protect sensitive information by monitoring and controlling access to sensitive data.
The attack surface for data loss includes perimeter resources, email, instant messaging, removable devices, social media, and third-party services. There are numerous other ways that data can be stolen or leaked, but these are in widespread use and difficult to monitor for anomalous and shady behavior.
What Is This DLP of Which You Speak?
DLP is a set of practices, tools, and strategies designed to prevent the unauthorized transmission or leakage of sensitive and confidential information from an organization. The goal is to keep personal, private, confidential, proprietary, and other vital information from being stolen, or even sent out unintentionally.
One reason that monitoring data loss is difficult is that items such as Social Security numbers, national insurance numbers, and credit card information can easily be modified: A monitor looking for xxx-xx-xxxx, for example, can be tricked by making it 0xxxxxxxxx1 or some other simple technique. And this is where other DLP techniques come into play.
How Does DLP Prevent Different Types of Cyberattacks?
Cyberattacks aren't always from the outside, and they aren't always initially malicious. This is important to keep in mind, especially with the increase in the remote workforce, a factor that has forced DLP to evolve. In an insider threat, someone with legitimate access can unintentionally leave a Web-facing resource unsecured, or accidentally send a confidential email to the wrong party, eliciting a malicious response from the outside. So, thinking outside the "cyberattacks always come from bad guys" box is important in a proper and layered approach to data security.
Here are a few ways DLP can be used to prevent cyberattacks:
Mitigating insider threats. Insider threats, whether intentional or accidental, can be mitigated through DLP, as it monitors and restricts data access and sharing based on predefined policies.
Ensuring compliance with regulations. Compliance is not the same as security, but it's a great way to provide a viable security baseline for organizations. DLP helps organizations adhere to data protection regulations, such as GDPR or HIPAA, by ensuring that sensitive data is handled in compliance with the law.
How DLP Works
The core principles of DLP revolve around protecting sensitive data from unauthorized access, sharing, or leakage. These principles guide the design, implementation, and operation of DLP systems. Here are some of these core principles:
Identification and classification of sensitive data. This principle involves identifying and classifying sensitive data within an organization such as personally identifiable information (PII), financial data, intellectual property, and proprietary business data.
Policy creation and enforcement. DLP policies specify rules and actions - such as blocking data transfer, encrypting data, alerting administrators, or quarantining data for review - that are triggered when sensitive data is detected.
Content inspection and contextual analysis. Content inspection techniques analyze content to identify sensitive information using predefined patterns, regular expressions, and sometimes machine learning algorithms. Contextual analysis considers the context, such as user roles and permissions, in which data is being accessed or shared.
User and entity behavior analysis (UEBA). By incorporating behavioral analytics to understand normal patterns of data usage and user behavior, DLP solutions can detect anomalies that might indicate a data breach or insider threat.
Endpoint protection. Protecting data at endpoints (computers, laptops, mobile devices) means preventing users from copying, printing, or sharing sensitive data without proper authorization.
Types of DLP Solutions
The solution you choose will depend on the attack surface that your risk assessment has determined to be worth monitoring. A few of the most common solutions are cloud-based, network-based, and endpoint-based DLP.
Cloud-based DLP monitors data activity in cloud environments and prevents data leaks in cloud storage and applications. Such solutions are designed to help organizations identify, classify, and protect sensitive data within their cloud environments.
Network-based DLP solutions monitor network traffic to detect and prevent data leaks, ensuring that sensitive data in motion is protected by automatically encrypting it. This encryption helps safeguard the data as it moves throughout the network, providing increased visibility into its usage, timing, and users involved.
Endpoint-based DLP is installed on individual devices and monitors data activity on those devices, focusing on monitoring and controlling the movement of sensitive data via file transfers, email communications, instant messaging, and Web browsing. For a remote workforce, priorities include ensuring that the devices have the proper permissions to ensure users or threat actors can't change the program, while still receiving and installing policy and program updates in a timely manner.