What are the 3 main objectives being solved by DLP?

Data Loss Prevention (DLP) The practice of identifying and stopping data breaches, exfiltration, or avoidable destruction of sensitive data is known as data loss prevention (DLP). DLP is used by organizations to safeguard their data, ensure compliance with laws, and protect it.

The phrase "DLP" refers to protecting enterprises from both data loss and data leakage. Data loss is the term used to describe a situation in which crucial data is lost to the business, such as during a ransomware attack. The focus of data loss prevention is to stop the unauthorized transmission of data across organizational boundaries.

Organizations typically use DLP to:

• Maintain the privacy of personally identifiable information (PII) and abide by all applicable laws.
 
• The importance of protecting intellectual property for the organization.
 
• Obtain data visibility in large corporations.
 
• Secure the workforce's mobile devices and uphold security in BYOD settings.
 
• Securing data on distant cloud platforms.

DLP Has Three Primary Applications

The three major goals of data loss prevention all address frequent pain points for many enterprises: personal information protection and compliance, intellectual property (IP) protection, and data visibility.

• Protection of personal data and compliance : Are personally identifiable information (PII), protected health information (PHI), and payment card information (PCI) collected and stored by your company? If so, you are probably subject to compliance rules like HIPAA (for PHI) and GDPR (for EU citizens' data), which demand that you safeguard sensitive customer data. DLP can recognize, categorize, and tag sensitive data, as well as keep an eye on the events and activities that surround it. The data needed for compliance audits is also provided by reporting capabilities.
• IP Protection : Does your company possess significant intellectual property, trade secrets, or state secrets that, if lost or stolen, could harm its financial stability and reputation? Intellectual property can be categorized in both structured and unstructured forms using DLP tools like Digital Guardian, which employ context-based categorization. You can prevent the unintentional exfiltration of this data by putting policies and controls in place.
• Data visibility : Does your company want to have more insight into the flow of data? You can see and track your data on endpoints, networks, and the cloud with the use of an all-inclusive business DLP solution. This will provide you with insight into how individual employees within your company engage with the data.

While these are the three core use cases, DLP can also address several other problems, such as advanced threats, user and entity behaviour analysis, Office 365 data security, insider threats, and user and entity behaviour analysis.

Data leakage causes

There are mainly three reasons for data leaks:

• Insider threats are caused by an attacker who has gained access to a privileged user account, abuses their credentials, and tries to move data outside of the company.
 
• Attackers' intrusion—sensitive data is often the target of cyberattacks. Using phishing, malware, or code injection tactics, attackers breach the security perimeter to access sensitive data.
 
• Unintentional or careless data exposure: Many data breaches are caused by employees who leave private information lying around, give data online access, or fail to impose access restrictions following company regulations.

Data Leakage Avoidance

Standard security tools can be used to protect against data loss and leaks. An intrusion detection system (IDS), for instance, can warn when an attacker tries to access sensitive information. Attackers can be stopped from compromising sensitive systems by antivirus software. Any unauthorized person cannot access systems that store sensitive data without being blocked by a firewall.

If you work for a large company, you might use specific DLP tools or solutions to protect your data. The Security Operations Center’s (SOC) tooling can also help with DLP. For instance, a Security Information and Event Management (SIEM) system can be used to identify and correlate events that could indicate a data leak.

Components of a Data Loss Solution

Securing data in motion:  technologies set up at the network edge can examine traffic to find sensitive information sent against security rules.

Securing endpoints—Information 

transit between users, groups of users, and outside parties can be managed by endpoint-based agents. Some endpoint-based systems can give users feedback while blocking real-time attempts at communication.

Securing data at rest: access  control, encryption, and data retention policies can secure archived organizational data when it comes to data security at rest.

Securing data in use: Some DLP systems may track and highlight inappropriate actions that users may take when interacting with data, either knowingly or unknowingly.

Data identification 

is essential in deciding whether or not it needs to be secured. Sensitive data can be identified manually by using rules and metadata or automatically using methods like machine learning.

Data leak detection:
• it identifies data transfers that are unusual or suspicious using DLP solutions and other security tools like IDS, IPS, and SIEM. These options also notify security personnel of potential data leaks.

DLP solutions and file security solutions

A DLP plan should include file security solutions like the Imperva File Firewall. These tools protect both data in use and data at rest, and they also look for file-based data leaks.

Data leaks are prevented by the Imperva File Firewall due to the:

• All sensitive file access is being monitored, and detailed usage information including user, department, and file accessed, file type, and operation response time is being recorded.
 
• Providing notifications for and automatically blocking file actions that are against security regulations.
 
• Using machine learning to identify unusual or suspicious user activity to identify insider threats.
 
• Preventing common file access patterns from being detected and used to mitigate ransomware attacks.
 
• All file operations will be reviewed and reported on for compliance and investigative needs.

 

FAQs

What exactly are DLP solutions?

Data Loss Prevention (DLP) Definition

A comprehensive DLP solution provides the information security team with complete visibility into all data on the network, including data in use (securing data being used by an application or endpoint through user authentication and access control).

What are the three types of data loss prevention?

The three main types of data loss prevention software include network DLP, endpoint DLP, and cloud DLP.

What are the main objectives of the data loss prevention API?

Data loss prevention solves three main objectives that are common pain points for many organizations: personal information protection and compliance, intellectual property (IP) protection, and data visibility.

What is the main purpose of DLP in the bank?

Using a variety of software tools and data privacy practices, DLP aims to prevent unauthorized access to sensitive information.