Introduction: What Is Data Loss Prevention (DLP)?
DLP, or Data Loss Prevention, is detecting and preventing data exfiltration, breaches, and unauthorized use or destruction of sensitive data.
Data breaches have become rampant since 2020 due to the work-from-home trend and emerging sophisticated cyber-attacks. In the third quarter of 2022 alone, approximately 15 million records were exposed worldwide due to data breaches.
Organizations must put measures in place to stop the unauthorized use and malicious movement of data. This is especially true, considering data breaches happen every 39 seconds on average. With 66% of small to medium-sized companies experiencing cyber-attacks in 2022, only those with stringent preventative measures against data loss will survive.
Many organizations implement DLP as part of their overall cybersecurity strategy. This explains why companies include Data Administrators and Scientists when building a cybersecurity team. It helps them identify unusual patterns and illicit activities, and meet regulatory compliance measures.
If protecting personally identifiable information (PII) and other confidential business information is critical to your business or career, you should consider data loss prevention.
Cybrary has a wide range of free resources for individuals and employees in small to large-scale enterprises. You can take theoretical courses and hands-on challenges on data security, including compliance requirement tests like GDPR and PCI DSS, among others.
Why Is Data Loss Prevention Important for Businesses?
Companies suffer huge reputational damages from data losses. For example, an Intel study revealed 68% of data breaches warrant public disclosure. Not implementing data loss prevention measures could damage a company's reputation, credibility, and consumer trust.
Data loss can also impact your business's financial health. As per IBM's Cost of Data Breach Report 2022, the global average of the cost of data breaches reached an all-time high of $4.35 million.
Data loss prevention is critical in protecting your data and intellectual property and maintaining regulatory compliance. DLP systems ensure that confidential or classified data belonging to your company is not handled carelessly or accessed by unauthorized users.
How Does DLP Work?
Data Loss Prevention software monitors, detects, and prevents sensitive data from leaving a company. This includes monitoring data entering corporate networks and trying to exit the network.
DLP solutions can use different techniques to detect sensitive data. Among these techniques are:
1. Regular Expression (RegEx) Matching
This is the most popular data loss prevention technique, which involves analyzing content to identify specific rules. For example, suppose an HTTP response leaving a company database contains a 9-digit number. In that case, the DLP system classifies the text string as likely to be a US social security number PPI. The same applies to a 16-digit number which could be a card number.
However, they can be susceptible to high false positive rates without checksum validation to pinpoint valid patterns.
2. Structured Data Fingerprinting
This procedure generates a unique digital "fingerprint" that can be used to identify a specific file, similar to how individual fingerprints can be used to identify individual people. DLP software will scan outgoing data for fingerprints to see if any match confidential files or if they’re properly protected.
3. Keyword Matching
DLP software scans user messages for specific words or phrases considered sensitive and blocks messages containing them. Companies can block outgoing emails containing confidential business information, such as financial reports, by using keywords or phrases that may appear in such documents.
4. File Matching
A hash is a unique string of characters used to identify a file. Hashes are generated by hashing algorithms, producing the same output whenever given the same input.
In this type of data loss prevention, hashes of outgoing files are compared to those of protected files. This helps a company detect when confidential information is leaving the network.
5. Exact Data Matching
This compares data to exact data sets that hold specific information that should be kept under organizational control. This method produces a few false positives, but it does not work for files that have many similar but not identical versions.
6. Pre-Built Categories
This involves categorization with dictionaries and rules for commonly used types of sensitive data like credit card numbers.
7. Statistical Analysis
In this data loss prevention method, the company uses machine learning (ML) and other statistical analysis methods like Bayesian analysis to detect policy violations in secure content.
There are many DLP solutions in the market today. Companies use these tools to execute different types of content inspection, depending on their needs. In some cases, a company might use specific systems designed for DLP, while they could also apply third-party technology or suites that aren't specifically for DLP.
To verify the precision of a DLP solution's content engine, pay attention to the types of patterns that each solution can successfully identify against a real corpus of sensitive data.
Types of Data Loss Prevention (DLP)
Since attackers can steal data in various ways, the right DLP solution includes detection techniques that cover the various ways data can be leaked.
The types of data loss prevention solutions include:
1. Network DLP
Network DLP gives you greater network visibility. It can identify when critical business data is being sent in violation of your company’s information security policy.
This enables the company to allow, flag, audit, encrypt, quarantine, or block such suspicious activities. This includes monitoring email, messages, file transfers, and similar web activities.
Network DLP can also come in handy when creating cybersecurity policies and procedures to reduce data loss risks and ensure regulatory compliance.
In addition, Network DLP can help establish a database that keeps track of who accesses sensitive data, when it is accessed, and where the data moves on the network. This ensures your cybersecurity team has comprehensive visibility into every bit of network data, whether in use, motion, or rest.
2. Cloud DLP
Cloud DLP is essential to ensure that business-critical workloads are not lost, leaked, or mishandled. This is especially essential considering the increase in cloud adoption among businesses. Cloud DLP solutions maintain a list of authorized cloud applications and users with clearance to access confidential data.
Hence, these solutions protect data stored in the cloud by encrypting private data and ensuring it is sent to only authorized cloud applications. Modern cloud DLP tools can identify, classify, and modify sensitive data before sending it to a cloud environment. This protects the data from insider threats, accidental exposure, and cyber-attacks.
In addition, Cloud DLP technologies track each time confidential cloud data is accessed, along with the user's identity. It can then notify your cybersecurity team of any unusual activity or policy violations.
3. Endpoint DLP
Endpoint DLP solutions keep an eye on the computers, servers, laptops, and mobile devices your business uses, moves, and stores sensitive data.
This helps prevent the loss or illegitimate use of your sensitive data.
Endpoint data loss prevention solution can help your business classify confidential, regulatory, or proprietary data to simplify reporting and compliance requirements.
Data Loss Prevention Tools and Technologies
DLP tools and technologies help protect your company’s sensitive data while it’s in use, in motion, and at rest.
Data in use implies security data in applications or endpoints while it is actively processed. This is achieved by authenticating users and controlling access to confidential data.
Protecting data in motion involves encrypting data to ensure that confidential data is protected while being transmitted across a network.
When at rest, DLP technologies are used to safeguard data kept in databases, the cloud, or other storage devices like backup tapes and endpoint devices.
Top DLP Software in Enterprise-Level Applications
Here are the top data loss prevention tools that prioritize secure archival:
- Symantec Data Loss Prevention by Broadcom
- Barracuda Backup
- Arcserve UDP
- Google Cloud Data Loss Prevention
- Trend Micro XDR
- McAfee Total Protection for DLP
- Spirion Data Privacy Manager
- Endpoint Protector by CoSoSys
- Code42
- Nightfall.ai
Others include Digital Guardian DLP, Forcepoint DLP, Palo Alto Networks Enterprise DLP, and GTB Technologies DLP.
7 Factors to Consider Before Choosing a DLP Solution
Before choosing a DLP vendor, you should understand whether:
- The vendor supports the current operating systems your company uses
- Is your data structured or unstructured?
- The type of threats the vendor defends against and the technologies the DLP solution integrates with
- Will the provider classify data, or will that be done by the users?
- The compliance regulations the vendor supports
- Are there measures and deployment options to reduce downtime?
- Will there be additional staff to support the DLP integration?
Generally, you’ll find four critical components in a DLP tool suite – a central management server, cloud support, network monitoring, and endpoint integration. Advanced analytics and data classification are other essential features to look out for.
Everything can be integrated into a single server or appliance except the endpoint agent if it's a small deployment. On the other hand, multiple distributed pieces may be used in larger deployments to cover various infrastructure components.
With this tool, businesses can always know where their sensitive data, intellectual property, customer data, financial information, and more—are located. It enables organizations to streamline data discovery and evaluation to respond quickly to any problem.
Best Practices for Data Loss Prevention
The best practices listed below can help businesses make the most of their DLP investment and ensure the solution fits with their current security policies and procedures:
- Set Your Goal: It's important to set clear goals for your data loss prevention program. Do you want to protect intellectual property or have better network visibility? Maybe you want to control how every sensitive data moves or do this to meet regulatory requirements. Setting a clear objective will help you choose the type of data loss prevention solutions to use, such as network, cloud, or endpoint DLP.
- Ensure DLP Solutions Align With Your Cybersecurity Architecture and Strategy: Your organization should consider any current security protocols, such as firewalls or monitoring systems, that might be used to supplement this new capability. Additionally, the organization must ensure that the DLP solution is completely integrated into its cybersecurity architecture.
- Identify and Classify Data: Before building and deploying a comprehensive DLP policy, you need a data classification framework for structured and unstructured data. Although DLP software automates data classification, your employees will select and customize the categories. To identify key data categories, DLP software can scan the data using a pre-set taxonomy, which your organization can still customize later. Data security categories include internal, public, confidential, personally identifiable information (PI), intellectual property, regulated data, financial data, etc. Doing this will provide a better understanding of the data that would cause the most damage if compromised.
- Manage Access: Access to sensitive data, and its use should be based on a user’s responsibilities and roles. Your System Administrators can do this easily by leveraging DLP tools and technologies. They can assign the right authorization levels to users based on the type of data they should handle and their access levels.
- Provide Change Management Guidelines: The agreed-upon configuration of a tool should be recorded and subsequently audited several times a year. Cybersecurity teams should frequently communicate with vendors and support teams about configurations and new features to maximize the tool's functionality and verify its use in the organization's environment.
- Educate and Train Employees: Data loss prevention is an ongoing process. This makes your employees a vital part of the program. As such, educating and training your employees on the value of data security and the impact of data loss on your company is essential.
Conclusion
The impact of a data loss on a business is catastrophic. Due to the increased rate of data breaches and more sophisticated attacks, organizations must put measures in place to prevent financial and reputational damage.
Cybrary simplifies the process of training your employees, allowing them to learn from real-world cases without leaving their daily duties. We have a comprehensive catalog of training resources on data security, recovery, and backup. Through theoretical courses and practical challenges, employees can learn critical data loss prevention procedures. Learn for free now.
