Defining Data Loss Prevention (DLP)
Data loss prevention (DLP) is a security strategy that allows your organization to control how sensitive data can be shared across networks and endpoint devices. Sensitive data needs to be protected because its exposure could negatively impact the data subjects. As such, data protection laws, like the General Data Protection Regulation (GDPR) or the California Consumer Privacy Act (CCPA), require adequate security measures to safeguard it. Your data loss prevention policy is part of how you protect this information. DLP is often implemented with the help of dedicated platforms and solutions.
Enterprise DLP solutions identify, monitor and protect:
- Data in transit (data in motion)
- Data at rest (data not being actively used)
- Data in process (data being stored or processed on a system)
These solutions can prevent unauthorized users from accessing intellectual property, customer information, medical and financial data, and other types of sensitive information. This is especially important given the increasing number of ways sensitive data can be exposed through social media, mobile devices, and cloud applications.
Data loss prevention programs are widely used in industries like healthcare, financial services and government agencies for data security. However, they can be used by any company with sensitive data to protect — including retail businesses, education providers and even individuals with personal information on their computers or other devices.
DLP tools often integrate with broader security platforms, such as security information and event management (SIEM) systems. In this setup, DLP alerts are fed into the SIEM for centralized logging, correlation, and monitoring alongside other security events.
Types of Data Threats: Causes of Data Leakage
As a business, you must protect your data against various types of security threats. Understanding these threat vectors is crucial for implementing an effective DLP program.
Cyberattacks
Cyberattacks are deliberate attempts by hackers to gain unauthorized access to systems and data. They can take many forms, including SQL injection, denial of service (DoS), and brute force attacks, all of which exploit vulnerabilities to steal or damage data.
Malware
Malicious software, or malware, comes in many forms, such as viruses, worms, and Trojans. Once installed, malware can corrupt, steal, or delete sensitive data. It may also spread to other systems within the network.
Insider Risks
An insider threat is any action or event by someone within the organization — employees, contractors, or business partners — that could result in unauthorized access to, disruption, or destruction of information systems or assets. For example, an insider within an organization leaks sensitive information to unauthorized third parties.
Unintentional Exposure
Humans are far from perfect and are the most common reason for data leaks — almost 75% of cyber incidents are caused by negligence or poor cyber hygiene. Unintentional exposure occurs when sensitive information is inadvertently made accessible to unauthorized individuals. This can happen through misconfigured databases, improper data handling, or accidental sharing of data in public forums or unsecured channels.
Organizations’ use of social media, mobile devices, and cloud applications has introduced several new vulnerabilities that make it easier for employees to accidentally share proprietary data with the public.
Phishing
Phishing attacks deceive individuals into providing personal data, such as login credentials or financial details, like their card information or social security numbers. Attackers use emails, fake websites, or messages that appear legitimate to trick recipients into disclosing confidential data. Often, this stolen data is used to gather more information, which is then used for bigger breaches.
Ransomware
Ransomware is a form of malware that encrypts the victim’s data. The threat actor then demands payment for the decryption key.
These attacks can paralyze an organization by locking critical data and systems and lead to significant financial and operational impacts.
Understanding the different types of data threats enables you to better defend against data breaches and ensure robust security practices. Implementing comprehensive DLP solutions can help mitigate these risks and protect sensitive information from unauthorized access and exposure.
How Does DLP Work?
A DLP solution scans, detects, monitors, and protects proprietary data to prevent unauthorized access, sharing, or leaks. It works by discovering and classifying sensitive data across endpoints, networks, and cloud environments.
Data discovery is a process through which you find out what data you have, including identifying shadow data that you own but aren’t aware of. Data classification is the next step, where you identify sensitive data and categorize information based on the level of protection it needs. Publicly available data might not need as much protection as sensitive data or personally identifiable information (PII). This means you need different rules and policies to govern and secure them.
Using the data category, your organization defines policies and rules that the system enforces to control data handling. The data leakage prevention software compares data against this list of rules.
For example, you could create policies based on the content of messages. If your company has confidential information about its clients, you could block certain words like “client” or “confidential.” You might have rules to prevent unauthorized data transfers to stop the leakage of sensitive data. The DLP tool monitors your systems and network to see if someone tries to transfer a document that’s been classified as sensitive. If they do, the process is stopped and an alert is sent out to the security team.
To secure data at rest, you would use data encryption, masking, segmentation, and monitoring measures. Securing data in use would involve endpoint monitoring, clipboard and print control, application control, peripheral device restrictions, etc. Data in transit would require network monitoring, email security, and blocking unauthorized protocols or channels. You’d also monitor cloud data, websites, and external servers.
While DLP solutions don’t directly handle data retention policies, they can help you implement them by identifying sensitive data that would need to be deleted after use. If you integrate the DLP solution with your governance platform, it can trigger an action such as quarantining the data or marking files for deletion.
Once you’ve created some policies for your DLP, it will work behind the scenes. It’ll use your rules to identify any unauthorized transmissions or storage of sensitive information and prevent them from happening.
Data loss prevention software can be installed on all endpoints used within your organization. That gives you visibility into all your important data and prevents it from leaving the device without authorization. It can also be used as part of an email service provider’s security suite to analyze incoming and outgoing emails for sensitive information.
The solution also continuously monitors data in use, in motion, and at rest, detecting and flagging policy violations. Automated responses, such as blocking transfers or encrypting data, help mitigate risks. Your DLP solution also provides alerts, reports, and auditing capabilities to ensure regulatory compliance and policy adherence.
Types of Data Loss Prevention Strategies
Storing sensitive data is no longer done on local machines and networks. Modern organizations store structured and unstructured data in the cloud more than on-premise, which means it’s shared over networks. As a result, your potential for data exposure grows. Therefore, you need to implement appropriate DLP strategies tailored to different environments to protect sensitive data.
Here are the three primary types of DLP solutions:
Network DLP
Network DLP solutions monitor and secure data in motion across your organization. They inspect network traffic to detect sensitive data transfers, and prevent unauthorized or accidental data loss. These data loss prevention solutions ensure that sensitive information is not sent outside the organization’s perimeter without proper authorization. They can block, quarantine, or encrypt data transmissions based on predefined policies.
Endpoint DLP
This form of DLP focuses on protecting data on endpoints, which are end-user devices, such as laptops, desktops, and mobile devices. This strategy involves monitoring and controlling data at the device level to prevent unauthorized access, use, or transfer of sensitive information. Endpoint DLP solutions can restrict actions like copying data to USB drives, printing confidential documents, or uploading files to unauthorized cloud services.
Cloud DLP
With the increasing adoption of cloud services, it’s crucial to prevent data loss from the cloud. Cloud DLP solutions safeguard data stored and processed in cloud environments, where they monitor and control access, usage, and sharing. They enforce security policies and prevent data theft in cloud-based ecosystems, applications, and services.
The Importance of Data Leakage Prevention
DLP safeguards sensitive information and ensures regulatory compliance. It helps your business prevent unauthorized access, sharing, data exfiltration, and leakage of confidential data. That helps protect your intellectual property and maintain customer trust.
These solutions continuously monitor your systems, detect potential threats, and enforce security policies to mitigate risks. DLP implementation also helps you comply with data protection regulations like GDPR and CCPA to reduce the likelihood of costly data breaches and legal penalties. In essence, DLP helps you maintain data integrity, security, and your reputation.
Many businesses have implemented modern and intuitive DLP to help them protect their sensitive information from leaving the company’s control. Many more are considering implementing DLP because they’re worried about being fined for noncompliance with GDPR regulations.
And, fines aren’t the only way illicit transfer of data outside your business can cost you.
Cost of a Data Leak
The estimated loss to businesses through cyberattacks is supposed to be 9.5 trillion USD in 2024, rising to 10.5 trillion USD in 2025.
Unauthorized access to data can be extremely costly for your business. It impacts both financial and reputational aspects. The average cost of a data breach includes breach detection and response expenses, legal fees, regulatory fines, and the cost of notifying affected individuals.
Additionally, you may face significant losses due to business disruption, customer churn, and damage to brand reputation. Investing in robust data protection measures, including DLP solutions, can help mitigate these risks and reduce the potential costs associated with data breaches.
DLP Best Practices
Implementing data loss prevention effectively requires a strategic approach. Here are some recommended guidelines to enhance your DLP efforts:
Identify and Classify Sensitive Data
The first step is to identify and classify sensitive data within your organization. Understand what data is most critical and where it resides. Categorize it according to sensitivity levels to prioritize protection efforts.
Develop Comprehensive Policies
Establish comprehensive DLP policies that define how data should be handled, shared, and protected. Ensure these policies are aligned with regulatory requirements and industry standards.
Educate and Train Employees
Regularly train employees on security practices and the importance of DLP. Ensure they understand the policies and procedures, and also how to recognize and respond to potential threats.
Utilize Encryption and Access Controls
Implement strong encryption methods to secure data both in transit and at rest. Use access controls to ensure only authorized personnel can access sensitive information, and regularly review permissions.
Monitor and Respond to Data Loss Incidents
Continuously monitor data access and transfer activities to promptly detect and respond to potential security incidents. Implement automated alerts and response mechanisms to address violations swiftly.
Regularly Review and Update Policies
DLP policies and strategies should be regularly reviewed and updated to adapt to new threats and changes in the organizational environment. Conduct periodic audits to ensure compliance and effectiveness.
By following these best practices, you can enhance your data protection measures, reduce the risk of data breaches, and ensure compliance with data privacy regulations.
Trends Driving DLP Adoption
Rise in Data Breaches
Data security is becoming more sophisticated with the use of AI, which can intelligently monitor and respond to unusual activity. Unfortunately, this smart tool is also accessible to threat actors, who use it to create personalized threat vectors. As the frequency and sophistication of cyberattacks increase, DLP systems help protect sensitive information from unauthorized access and theft.
Expanding Role of CISOs
Chief Information Security Officers (CISOs) are playing a more critical role in information protection strategies. They understand the role of prevention in data security. With data protection measures in place, you can prevent and mitigate potential data loss instead of reacting to it after the fact. As such, CISOs drive the adoption of comprehensive DLP measures to safeguard organizational data.
Compliance Mandates
Regulatory requirements like GDPR and HIPAA mandate stringent data protection practices. and they constantly evolve to keep up with technology and threats. If you’re found in breach of these laws, you can face legal action as well as penalties. DLP solutions help you stay compliant and avoid hefty fines.
Complexity of Data Environments
In the past, all your data was stored on servers in your premises. It was used on software and applications installed on endpoints that stayed in the office. Now, however, technology is decentralized. Cloud data is processed in software-as-a-service (SaaS) applications that run on cloud infrastructure. These complex supply chains and processes require advanced DLP strategies to protect data across diverse and distributed environments.
High Value of Stolen Data
Data is the new oil. Everyone wants it, whether for business purposes (e.g. more targeted marketing) or nefarious ones (e.g. stealing login credentials to gain access to the user’s money). The fact that data is in so much demand creates the need for effective DLP solutions to prevent data breaches and protect valuable information assets.
Cybersecurity Talent Shortage
There is a national talent shortage of 225,200 skilled cybersecurity workers across the United States. This scarcity means more automated and efficient DLP systems are needed to mitigate risks and ensure data security.
Combine BigID With Your DLP Solution For Comprehensive Data Security
Often, prevention is better than trying to fix the situation. Choosing a DLP tool to work together with BigID’s Access Intelligence App helps you highlight vulnerable and high-risk data at a glance. It uncovers vulnerabilities so you can prioritize remediation efforts to secure them.
BigID accelerates DLP through consistency, coverage, and accuracy and alleviates your tool’s burden. It standardizes sensitivity classification definitions for your organization to consistently enforce policies and controls across all of your information, regardless of where it lives.
The platform provides hundreds of OOB classifiers and customizable ML-based classifiers to categorize more data more accurately and at scale. This enables the pre-remediation of your data to prevent unauthorized or unintended loss.
Would you like to learn more about how BigID’s Data Intelligence platform can help bridge the gap between your DLP tools?
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