Essential Data Loss Prevention Best Practices Every Firm Should Know

Data is the most valuable resource any company possesses. When this is lost – whether through carelessness or a malicious attack – the consequences will be severe. This can range from a loss of trust among customers to regulatory fines and class-action lawsuits. In some cases, it could even threaten the future of the entire business. As such, having a clear plan for data loss prevention (DLP) is an essential part of any enterprise’s security policy.

Data loss is among the most damaging challenges for any business, and this goes far beyond any downtime firms experience while backups are implemented. It could result in confidential proprietary information being leaked to competitors or sensitive customer financial details being used by fraudsters. If data does end up in the hands of criminals, it can also be used as the basis for extortion.

Broadly speaking, data protection refers to every activity a business undertakes to safeguard the sensitive information it possesses. This does not only cover loss prevention, but also the steps firms take to make sure customer data is not misused. For example, regulations such as the EU’s General Data Protection Regulation (GDPR) set strict limits on the collection of data and how firms must obtain user consent for its processing and storage. 

Naturally, preventing a data leak must play a major role in this. Data breaches, whether accidental or deliberate, are a major financial burden for businesses, with the average incident costing $4.35 million in 2022. There are a wide range of issues that contribute to this, from direct downtime through to reputational damage and regulatory action. Many companies, especially smaller firms, never fully recover from these costs.

While avoiding the cost of a data breach is perhaps the most obvious reason to build a data loss protection strategy, this should not be the only consideration. There are several other critical reasons why it’s important to have a strong data loss prevention policy. These include the following.

Maintain compliance – Ensuring firms keep in compliance with data protection regulations around the world is essential, especially as these have tightened significantly in recent years. GDPR, for example, allows regulators to levy fines of up to either €20 million or four percent of global turnover for breaches – whichever is higher. Meanwhile, if you’re collecting customer credit card details, for instance, PCI DSS rules have stringent requirements for safeguarding this information.

Protect brand reputation – As well as regulators, customers are also highly protective of their personal data and will make this a key factor when making decisions. According to McKinsey, 85 percent of consumers say that knowing a company’s data privacy policies is important before making a purchase, while 53 percent will only do business with firms that have a reputation for data protection.

Consumer trust is also easy to lose. For instance, one study by SurveyMonkey found more than half of people in the US (55 percent) would be less likely to continue to do business with brands that are victims of a cyberattack. 

Protect intellectual property – Another potential issue is the loss of confidential business data. This could be trade secrets or intellectual property that would be highly valuable to competitors, or research and development priorities that could allow other firms to gain an advantage. 

This type of data theft may be especially hard to stop if it is the result of an insider threat, such as an employee who has been bribed to steal data or someone who is leaving their role and plans to take sensitive data with them to their new employer. In these cases, individuals may well have legitimate access to information, so would be able to bypass many standard data security safeguards.

A key benefit of a strong data loss prevention strategy is that it can reduce your exposure to ransomware attacks. These have rapidly become one of the biggest threats any firm faces over the last few years, with figures from Statista showing 71 percent of companies globally were affected by this last year.

Effective solutions can prevent issues caused by traditional ransomware attacks, where data is corrupted or encrypted until a ransom is paid. But advanced tools can also guard against double extortion ransomware, where stolen data is used as leverage to convince firms to pay up.

In these cases, hackers threaten to expose or sell data unless paid, hoping firms will hand over a ransom to avoid public disclosure of a breach. This can be highly effective, so it’s no surprise it’s a popular tactic. According to Palo Alto Networks, a firm fell victim to double extortion attacks once every three to four hours in 2022, while Statista’s figures showed 62.9 percent of ransomware victims paid up, which only encourages criminals to continue launching such attacks.

Any good enterprise data loss prevention solution should start with a data discovery program. Firms can’t protect data they don’t know about, and in today’s sprawling network environment, it’s easy for important data to be hidden from view. Therefore, understanding what types of data you have, where it is stored and processed, and who will need to access it is a vital first step when formulating a data protection best practice strategy.

Once businesses have conducted a full audit for complete visibility into their data environment, the next step is effectively classifying it. Not all data has the same value, and attempting to apply the same level of protection to every piece of information will be expensive, time-consuming and disruptive. Therefore, knowing where to prioritize your efforts is essential when developing data loss prevention best practices.

Generally, data can be classified into three basic levels according to the level of risk involved in a breach – high, medium and low. Exactly which category certain types of data may fall into can differ depending on the individual business, but as a general rule, it works as follows:

High-risk data: This covers any data which is essential to the running of the business. If this data is lost, corrupted or stolen, it would have an immediate and serious impact on either the organization as a whole or individuals. Financial data, intellectual property and key operational data all fall into this category. As such, it requires the highest possible solutions to prevent unauthorized access.

Medium-risk data: This covers data that, while still private and for internal use only, would not represent an immediate material risk. Internal emails, operating procedures and product and supply chain documentation are usually placed here. Tools such as access controls are still necessary, but there is not typically a need for a constant, real-time monitoring and response plan.

Low-risk data: This usually includes information that is already available to the public, such as website information, or outdated information that has no commercial value, such as archives that are rarely, if ever, accessed.

As well as ensuring data is categorized correctly according to its value, businesses also need to protect it at each stage of the business process. There are three distinct states for any business data that will each require their own protection strategies, so it’s important to be aware of the following:

Data at rest: This is where your information will spend the majority of its time – in storage in either internal data centers or cloud services. Effective access controls and encryption are important in securing this information and preventing unauthorized activities. 

Data in motion: Data that is being transferred to and from applications or devices. This is usually more vulnerable than data at rest and so requires careful monitoring to ensure it is moving to approved locations and not being intercepted by efforts such as man-in-the-middle attacks. This also has different encryption requirements than data at rest, so strong network security is a must.

Data in use: Usually the hardest to protect, this covers information that is being actively processed. This is often where user error can lead to a data breach, while in many cases, it is required to be decrypted in order to be worked on. Strong identity management and employee training is the key to protecting this information.

Once businesses are able to successfully identify exactly what data they hold, where it is stored and what security priority it should be, they will be in a much better place to effectively protect it from cyberthreats. To do this, there are a few key steps to keep in mind.

Encryption is a must for any sensitive information. It might not prevent data loss by itself, but it does mean that if your business is compromised, there’s less chance that hackers will be able to use any stolen data. This needs to include both data at rest and data in motion and is a requirement for standards such as PCI DSS, which mandates cardholder data be protected with this technology.

Strong control of who has access to your systems is critical in preventing data exfiltration. A key best practice is to adopt a position of ‘principle of least privilege’. This states that any employee should only have access to data that is required for their day-to-day job and not more.

Other access management essentials include the use of multi-factor authentication to minimize the risk of stolen credentials being used to access data, while full monitoring is vital to send immediate alerts if an unauthorized user attempts to login to a system, as well as to maintain a full audit trail.

User error continues to be a primary cause of data breaches. In fact, one report from the World Economic Forum in 2022 claimed as many as 95 percent of cybersecurity issues can be traced back to this. Mistakes can range from losing devices to IT misconfiguration or inadvertently sending sensitive details directly to hackers.

Technical solutions can help address these issues, but they can’t stop them completely. Therefore, comprehensive user education must be a central pillar of any data loss prevention strategy. The key to getting this right is to make it an ongoing process and ensure there are multiple learning methods and follow-up checks used to ensure all rules are being followed. 

Hardening your systems against intrusion covers a number of facets. In addition to encrypting any data being used, businesses need to ensure all their applications are up to date in order to guard against newly-discovered vulnerabilities.

Activities such as patch management can often be more complex than they appear, especially for larger enterprises with sprawling, complex network infrastructure. However, failing to keep up with this can leave businesses seriously exposed to data theft, so ensuring the security team has a clear schedule for managing this is vital.

Firms must have a complete picture of how data is moving within their network and – crucially – when it’s leaving it. Large enterprises are constantly transferring data to and from cloud systems, suppliers and other partners, so this can be hard to keep track of, but if companies don’t have visibility it can make it easy for hackers to steal data from under their nose.

The best way to achieve this is with dedicated endpoint solutions that can sit on every device – from desktops to employee-owned smartphones to keep track of when data is removed. This should look at various factors, including what type of data is being moved, who is doing it and what the destination is. With the right tools, firms can then easily identify any activity that doesn’t look right and block potential data exfiltration before it happens.

As well as the right training and operational practices, you need the right cybersecurity technology tools to prevent data loss. There’s no one silver bullet to achieve this – instead, you need to take a defense in depth approach that covers everything from initial perimeter protection through to blocking data exfiltration attempts.

However, there are a few types of solutions that promise to play a key role in data loss prevention. It’s vital you understand how these work and what their limitations are in order to understand what they should fit into your strategy.

Intrusion detection and prevention systems (IDPS) promise to go beyond traditional firewalls to hunt for threats that have already breached the network perimeter. By monitoring and analyzing internal network traffic, they can identify unusual traffic patterns to unauthorized attempts to access sensitive data or applications.

For example, on a basic level, they can be configured to send alerts and block accounts if a certain number of unsuccessful login attempts are made. But more advanced features can also look at user profiles, study how applications typically use data, and take automated actions to quarantine potential malicious infections.

Dedicated endpoint detection and response (EDR) tools monitor every action taken on network endpoints – which may include desktop and laptops PCs, smartphones or even Internet of Things devices. They work in real-time to spot potential infections such as malware and ransomware that aim to steal data and shut them down before they have a chance to succeed.

Tools to monitor the network at this level are increasingly important as networks become less centralized and the boundaries get blurred. Remote workers using cloud tools and connecting to a corporate network remotely, for example, are increasingly common targets, so the ability to defend against threats at the device level is more important than ever.

Data loss prevention, or DLP software, aims to prevent data leakage by classifying a firm’s data and constantly monitoring how it is used. They are useful for gaining better visibility into where your information is and who is accessing it, as well as spotting if data protection policies and best practices are being ignored.

However, while a DLP tool can be very useful for guarding against an accidental data leak and is highly useful in maintaining compliance with key regulations, these solutions are often less effective at dealing with malicious threats. They are a more reactive solution that may not be able to keep up with the latest attack vectors, and can often be complex to manage and disruptive to day-to-day operations.

Today’s hacking groups have become extremely proficient at avoiding many standard defenses. But even if threats are able to evade detection and infect a firm’s systems, this does not mean the cybercriminals have won, this is where anti data exfiltration (ADX) software can come in.

Like EDR, this sits on the endpoint. However, its primary focus is to monitor all outgoing traffic looking for potential data theft 24/7. Using behavioral analytics and machine learning to build a full picture of a business’ normal activity, these automated tools can study data traffic, destinations and users to identify and automatically block any suspicious data transfer. Because they are not dependent on traditional methods like signature matching, they are much more effective at spotting data exfiltration attempts in progress than other tools.

This is particularly important in defending against threats such as double extortion ransomware, so should be an essential part of any enterprise’s strategy in today’s environment.