Stop malicious exfiltration with data loss prevention capabilities.Data Security Compliance Brief
Data Loss Prevention (DLP) is a strategy put in place by security organizations that prevents the leaking and potentially malicious exfiltration of secure data. According to the Information Systems Audit and Control Association (ISACA), implementing a robust DLP solution is crucial for detecting and preventing unauthorized data leakage and sharing, thus safeguarding sensitive information.
The organization goes on to say that it’s important to know locations where data exists, along with an indication of the functional areas of where to implement or enhance applicable security and privacy controls.
DLP is important for many reasons, not the least of which is the company’s bottom line. Stakeholders and/or shareholders have a vested financial interest in not seeing critical company data stolen and either held for ransom (which will cost a lot of money) or forever affect the reputation of the business (resulting in erosion of customer trust and a lot of money lost over a very short period of time).
Blocking an attacker from breaching a system or network is easier said than done, especially in the age of cloud security and operations. An effective DLP solution solves for two primary types of offenders: internal and external. Malicious actors who are also employees of a business certainly exist, but typically when an internal offender is the source of data leakage, it occurs unknowingly on the part of that source.
These days, pretty much everyone understands that sensitive information is transmitted through the cloud and back again many, many times. That’s just how we live today. More often than not, though, we don’t understand how data is transmitted or otherwise used in the organization.
Additionally, these organizations may be unaware of certain communication or workflow trends that could put an organization at unnecessary risk. For example, a business’ finance department might engage in a workflow whereby they transmit incredibly sensitive data through public communication channels like email or instant messaging.
External offenders typically know exactly what they’re doing: trying to break through the defenses of your company’s security organization and steal sensitive data and – as previously mentioned – hold it for ransom and/or sell it to the highest bidder on the dark web.
For these key reasons, it’s critical a DLP solution is able to detect when and where data is leaving and entering networks and help analysts prioritize protecting data that may be more sensitive than other data.
Let's take a look at some of the top reasons data at rest or in transit might "leak" off of endpoints, systems, and networks and into the hands of bad actors.
The benefits of a DLP solution are clear and add up to the ability to better secure data from inadvertent exposure and theft. Let's break down a few key benefits and how they specifically affect a network.
The ability to monitor network endpoint devices and analyze traffic and interactions for suspicious activity will accelerate visibility of an overall environment and improve security posture. Monitoring a network for data loss can also help to eliminate previously unseen blindspots – internally and among devices connecting to a network – that were just waiting to be exploited.
Identity and access management (IAM) is critical for a DLP solution and network security in general. IAM helps to ensure the right people are accessing the right endpoints or network systems. By instituting IAM policies on critical systems and endpoints, the network perimeter becomes harder to breach, which in turn can help the business remain in compliance with both internal and external regulatory standards.
Data classification should be as simple and straightforward as possible. Let's look at a tiered-structure example:
Based on this classification, it’s clear that storing the wrong data at the wrong level, or classification, could have potentially disastrous effects. If there is a situation where data of different classification levels must reside on the same server, intermixed data should be labeled and classified using the highest classification rating and thus protected accordingly. Automating this process will also help to ensure it occurs with efficiency and speed.
Implementing best practices for a DLP solution will help to calibrate it to a specific environment. According to ISACA, there are many best practices that will help to ensure a DLP strategy is deployed successfully: