Endpoint Data Loss Prevention: Protect Your Data Securely

A business’ endpoints are often its weakest link when it comes to data protection. In today’s environment, the number of devices is growing at a huge rate, making it hard for security teams to effectively manage their entire environment. This is particularly the case when they may not even have full visibility into all the endpoints on their network.

To tackle these issues, it’s important to have a comprehensive endpoint data loss prevention (DLP) strategy. Here’s what this involves.

Endpoint data loss prevention is an aspect of a DLP strategy that focuses on the various endpoints that connect to the network and are able to access and use company data. This includes desktop and laptop PCs, smartphones and tablets used by employees, as well as servers, virtual machines and embedded devices such as Internet of Things sensors.

They are particularly important when it comes to data security as they enable information to enter and leave the network. This makes them a critical target for hackers. Traditionally, these endpoints have been treated as entry points for cybercriminals, so security efforts primarily focus on outward-looking defenses to block this.

However, in today’s environment, a bigger concern is often how they can be used to remove sensitive information from the network. This is called data exfiltration and it’s a key priority for many of today’s ransomware gangs. If criminals are able to remove sensitive information from businesses, they can then demand money from victims in exchange for not releasing it publicly. This is known as double extortion ransomware, a tactic that has quickly become one of the most popular methods for hackers. Indeed, according to our research, more than nine out of ten ransomware attacks now seek to exfiltrate data.

To prevent this, firms need a comprehensive security solution in place to protect their endpoints. An effective strategy should include all the below features in order to successfully identify and block any data exfiltration attempts before they occur.

Not all data is equally valuable. The ability to classify data within a network to prioritize the most sensitive information – such as intellectual property, personally-identifiable information, financial details or health records – is a key part of any data security strategy. Once this has been done, DLP tools should be able to identify the most sensitive information to ensure that the highest security policies are being applied to it.

Full monitoring of all network activities, including data access, user accounts, and transfer destinations, is crucial in detecting intrusions and preventing data breaches. This analysis of vast amounts of data at the endpoint necessitates solutions to streamline the process and ensure that activities occur on the device rather than being sent back to central servers. Real-time execution is essential to avoid even small delays in identifying illicit activity rendering defenses ineffective.

There may be several telltale signs that a hacker or a malicious insider is attempting to exfiltrate data, and a good endpoint DLP tool should be able to look out for these. Possible red flags include repeated attempts to login to databases, accessing files that are outside a user’s normal responsibilities, or large file transfers to unusual destinations or that take place outside working hours.

When suspicious activity is detected, immediate action is crucial. Any attempts to exfiltrate data should be automatically blocked as soon as it is discovered. Alternatively, alerts can be sent for review by the security team, but this approach often leads to delays. Moreover, it’s essential to ensure that such systems avoid false positives that block legitimate traffic, as this could disrupt business operations significantly.

A robust endpoint DLP solution offers the primary advantage of safeguarding against malicious attacks like ransomware and insiders who aim to steal sensitive data. Once information exits the business network, it can be exploited for extortion, publicly disclosed to damage a company’s reputation, or sold on the dark web to the highest bidder.

The consequences of a data breach can be far-reaching and expensive. Businesses that fall victim to such an incident may incur the following expenses:

• Ransom payments to criminals
• Direct lost business as a result of loss of trust among customers
• Fines from regulators
• Class-action lawsuits
• Immediate remediation and investigation expenses
• Third-party experts
• Costs related to hardening systems for the future, such as new hardware and software solutions

Having a dedicated endpoint data loss prevention system is crucial for companies with a significant number of remote, hybrid, or mobile workers. These policies extend a company’s network beyond the traditional perimeter and often involve numerous employee-owned devices accessing data. Consequently, tools that can be effortlessly installed on these endpoints and function directly on the devices play a vital role in safeguarding against such vulnerabilities by reclaiming control over these assets.

There are a wide range of data loss prevention services available because the concepts behind this technology are not new. However, some legacy offerings may not be fully equipped to identify and address the most recent developments used by cybercriminals to find and exfiltrate data.

For example, some technologies still rely mainly on pattern recognition and signature matching to spot illicit activity. This may mean that more advanced techniques that do not leave these traces go undetected.

Therefore, advanced technologies that specialize in anti data exfiltration (ADX) will be indispensable. These technologies employ techniques such as artificial intelligence to construct a comprehensive profile of user behavior over time, enabling them to detect anomalous activity in real-time.

Additionally, it’s crucial to secure lightweight tools that can operate on any device, including mobile devices, and do not require data transmission back to central servers for analysis. This ensures that information remains secure at all times, even when users are outside the network’s perimeter, and does not disrupt the data flow by introducing an additional step where data is sent back and decrypted.

There are several key considerations firms must take into account when implementing an endpoint DLP solution. First and foremost, security professionals must ensure that the tools align with their overall security practices. This involves setting up DLP policy management tools that govern user interactions with data and determine the permissions users have. Without this, the tools won’t be able to detect telltale signs of a data breach, such as unauthorized access to sensitive information.

Another crucial aspect of endpoint DLP is reducing the risk of false positives. False positives can disrupt legitimate activities and cause unnecessary disruptions. To address this, tools like artificial intelligence and machine learning that develop an accurate picture of normal behavior over time are highly advantageous.

Lastly, DLP tools must be lightweight and unobtrusive enough to work seamlessly across all endpoints. When considering options, companies should ensure that their chosen solution is optimized for use on devices like smartphones.