Data Loss Prevention (DLP)

Data loss prevention (DLP) is a cybersecurity strategy that protects sensitive information from unauthorized access, disclosure, or exfiltration. Since it blocks extraction of sensitive data, organizations use it for internal security and regulatory compliance. DLP systems use a combination of people, processes, and technology to detect and prevent data breaches .

DLP systems can be applied across a variety of communication channels, including email, file transfers, and cloud storage. They can also be used to help organizations comply with regulations like the California Consumer Privacy Act (CCPA), EU General Data Protection Regulation (GDPR), and Health Insurance Portability and Accountability Act (HIPAA).’

Need for DLP

The threat of data breaches – incidents where protected is stolen, used, or viewed by an unauthorized individual – has rapidly increased as the world became more digital. DLP solution is essential to your risk reduction strategy, especially when it comes to securing endpoints like mobile devices, desktop computers, and servers.

With data threats, it’s a matter of when they’ll happen, not if they’ll happen. Choosing a DLP solution for your organization requires research and planning, but it’s time and money well spent to protect the sensitive data, personal information, and reputation of your brand.

Working Principle of a DLP Solution

Monitoring: DLP systems monitor data in use, in motion, and at rest. They can monitor network endpoint devices and analyze traffic and interactions for suspicious activity.

Detection: DLP systems use AI, machine learning, and antivirus software to detect suspicious activities. They compare content to an organization’s DLP policy, which defines how data should be labeled, shared, and protected.

Blocking: DLP systems block the transmission of sensitive data. For example, DLP software can block outgoing emails that contain certain words or phrases. Reporting: DLP systems can report on suspicious activities

Reporting: DLP systems can report on suspicious activities.

Types of Data Threats

Data threats are actions that can affect the integrity, confidentiality, or availability of your organization’s data, while a data leak exposes your sensitive data to untrustworthy environments.

Cyberattack: A cyberattack is a deliberate, malicious attempt to gain unauthorized access to computer systems (business and personal) and steal, modify, or destroy data. Examples of cyberattacks include distributed denial-of-service (DDoS) attacks, spyware, and ransomware. Cloud security, identity and access management, and risk management are a few ways to protect your network.

Malware: Malware, or malicious software—including worms, viruses, and spyware—is often disguised as a trusted email attachment or program (for example, an encrypted document or file folder). Once opened, it allows unauthorized users into your environment who can then disrupt your entire IT network.

Insider risks:  Insiders are people who have information about your data, computer systems, and security practices, such as employees, vendors, contractors, and partners. Misusing authorized access to negatively impact the organization is one example of an insider risk.

Unintentional exposure: Unintentional exposure occurs when employees unknowingly allow access to unauthorized users or viruses. Identity and access management tools help organizations control what users can and can’t access, and helps keep your organization’s important resources—like apps, files, and data—secure.

Phishing: Phishing is the act of sending fraudulent emails on behalf of reputable companies or other trustworthy sources. The intention of a phishing attack is to steal or damage sensitive data by tricking people into revealing personal information such as passwords and credit card numbers. They can target a single person, a team, a department, or an entire company.

Ransomware: Ransomware is a type of malware that threatens to destroy or block access to critical data or systems until a ransom is paid. Human-operated ransomware that targets organizations can be difficult to prevent and reverse because the attackers use their collective intelligence to gain access to an organization’s network.

Benefits of a DLP solution

DLP benefits begin with the ability to classify and monitor your data and include improving your overall visibility and control.

Classify and monitor sensitive data: Knowing what data you have and how it’s used across your digital estate makes it easier for your organization to identify unauthorized access to data and protect it from misuse. Classification means applying rules for identifying sensitive data and maintaining a compliant data security strategy.

Detect and block suspicious activity: Customize your DLP solution to scan all data flowing through your network and block it from leaving the network by email, being copied to USB drives, or other means.

Automate data classification: Automated classification gathers information, such as when a document was created, where it’s stored, and how it’s shared, to improve the quality of data classification in your organization. A DLP solution uses this information to enforce your DLP policy, which helps prevent sensitive data from being shared with unauthorized users.

Maintain regulatory compliance: Every organization must adhere to data protection standards, laws, and regulations like HIPAA, the Sarbanes-Oxley (SOX) Act, and the Federal Information Security Management Act (FISMA). A DLP solution gives you the reporting capabilities you need to complete compliance audits, which may also include having a data-retention plan and training program for your employees.
As an example, HIPAA places extensive data security requirements on all businesses that have access to, process, and store any protected health information. The organization defines guidelines, policies, and procedures for maintaining the privacy and security of individually identifiable health information. It also outlines offenses and civil and criminal penalties for failing to protect this data. DLP is vital for organizations that need to comply with HIPAA. It allows them to identify, classify, and tag data that is covered by regulations and ensure end-users are protected.

Monitor data access and usage: To keep threats at bay, you need to monitor who has access to what and what they’re doing with that access. Prevent insider breaches and fraud by managing the digital identities of employees, vendors, contractors, and partners across your network, apps, and devices. Role-based access control is one example of providing access to only the people who need it to do their jobs.

Improve visibility and control: A DLP solution gives you visibility into the sensitive data within your organization and helps you see who might be sending it to unauthorized users. Once you determine the scope of actual and potential issues, further customizations can be made to analyze data and content to strengthen your cybersecurity measures and DLP effort

Personally identifiable information (PII): PII is data that could potentially identify an individual or distinguish them from another person. This includes end-users’ email addresses, mailing addresses, and Social Security numbers, as well as IP addresses, login IDs, social media posts, and biometric and geolocation information. There are stringent regulations in place to protect this, such as GDPR, that grant people more rights around how companies handle their data and impose heavy fines for noncompliance and breaches.

DLP security enables businesses to classify, identify, and tag data and monitor activities and events surrounding it. It also provides the reporting capabilities that let organizations complete compliance audits.

Intellectual property (IP): Intellectual property includes software, proprietary data, and original works. IP owners need to ensure their digital assets are secure behind proper security protocols and defenses, including firewalls, restricted access privileges, and intrusion detection and prevention systems.

Malicious actors who gain access to intellectual property may cause severe losses by destroying irreplaceable information or code, copying protected assets and selling or distributing them on the Internet, and otherwise exploiting unauthorized access for their own gain.

DLP best practices

Follow these best practices to help ensure successful data loss prevention:

Identify and classify sensitive data. To protect your data, you need to know what you’ve got. Use your DLP policy to identify sensitive data and label it accordingly.

Use data encryption. Encrypt data that is at rest or in transit so unauthorized users won’t be able to view file content even if they gain access to its location.

Secure your systems. A network is only as secure as its weakest entry point. Limit access to employees who need it to do their jobs.

Implement DLP in phases. Know your business priorities and establish a pilot test. Allow your organization to grow into the solution and all it has to offer.

Implement a patch management strategy. Test all patches for your infrastructure to ensure there are no vulnerabilities being introduced into your organization.

Allocate roles. Establish roles and responsibilities to clarify who is accountable for data security.

Automate. Manual DLP processes are limited in scope and can’t scale to meet the future needs of your organization.

Use anomaly detection. Machine learning and behavioral analytics can be used to identify abnormal behavior that could result in a data leak.

Educate stakeholders. A DLP policy isn’t enough to prevent intentional or accidental incidents; stakeholders and users must know their role in protecting your organization’s data. Establish metrics. Tracking metrics—like the number of incidents and time-to-response—will help determine the effectiveness of your DLP strategy