How Does Data Loss Prevention Software Work?

With the growing rise of data breaches and insider threats, businesses need to employ as much security as they can afford. Security software, like employee monitoring software, firewall, and security information and event management (SIEM) systems all provide a level of security to business data. However, the level of security needed and the amount of privacy and compliance laws that need to be followed will determine which software products are needed. 

Most likely, a business will need to consider data loss prevention software or DLP as a security solution. DLP technology is a set of security tools that monitors computers, servers, networks, and workstations to watch if sensitive information is moved, deleted, copied, or modified. Having this type of software working on behalf of your company is crucial as it allows businesses to mitigate data risk and to catch anomalies before they become attacks. 

Read on to learn about DLP software and why you might use it for your data security:

What is Data Loss Prevention Software?

Data loss prevention software, or DLP, is a set of tools or technologies which monitor certain movements over a given network, at a managed endpoint device, at on-premise file services, or in cloud storage and cloud applications. 

The software actions range based on how it’s configured, which will be different for each company’s policy and rules around sensitive data protection. However, the majority of DLP software performs content inspection and contextual analysis of any data that is sent out of a company, moved on a network, used on the endpoint device, in on-premise file services, and in cloud applications.   

DLP technologies are categorized as Enterprise DLP and Integrated DLP. Enterprise DLP provides comprehensive agent software for the desired monitoring locations (i.e., desktops, servers, virtual machines, physical machines, etc) whereas an integrated DLP solution might be limited to secure email gateways (SEGs), email encryption, secure web gateways (SWGs), enterprise content management (ECM) platforms, data classification tools, data discovery tools, and cloud access security brokers (CASBs). 

How Does DLP Work?

DLP performs both content awareness protocols and contextual analysis. This is crucial when it comes to risk mitigation because many security solutions can only perform content awareness protocols, and therefore admins have limited insight and analysis when it comes to security alerts.

Context analysis allows the software not only to read the content but to also provide additional context so that administrators have more intelligence around potential security alerts rather than just being triggered to them. The context analysis feature will analyze the captured data and assess the contextual clues, mainly external factors like header, size, and format. 

Here are some of the content analysis techniques that can be performed and then used to trigger policy violations: 

  • Pre-built categories: Data can be assigned a category, which comes with its own set of rules and dictionaries. Data can be categorized and labeled as common sensitive data types, such as credit card numbers, PCI protection, financial data, and HIPAA. 
  • Rule-Based/Regular Expressions: This is the most common analysis technique in DLP. This involves engine-analyzed content that looks at specific rules, including 16-digit credit card numbers and 9-digit social security numbers. This is commonly the first-pass filter since configuration and processing are quick, but they are prone to high false-positive rates with missing checksum validation to identify patterns. 
  • Exact File Matching: Exact file matching does not analyze the contents; however, the hashes of the files are matched like a fingerprint to validate the file. This has a low false-positive rate, but it does not work for files that are similar but not identical (like verified copies). 
  • Statistical Analysis: This method uses machine learning and statistical methods like Bayesian analysis to find and alert to policy violations triggered in secured content. This requires a large amount of scannable volume or else it will be prone to false alerts. 
  • Conceptual/Lexicon: Conceptual or lexicon techniques rely on rules and dictionaries to alert on unstructured data that defy categorization. Needs to be DLP customized. 
  • Database Fingerprinting: Database fingerprinting is also referred to as Exact Data Matching, which looks at only exact matches from a live database/database dump. Ideal for structured data from databases. 
  • Partial Document Matching: This method looks for partial or completely matching files to weed out multiple versions of a document and multiple users. 

Data Loss Protection Solution Use Cases

There is a range of specified DLP use cases, businesses largely need it for data protection and data monitoring. Here are the top 6 use cases businesses should consider: 

1. Protecting Against Insider Threats

One of the biggest and most effective use cases for DLP solutions is to protect against insider threats. While DLP software can’t physically stop an attack from occurring, it can watch sensitive data and alert to admin improper actions around that data. 

Therefore, DLP software like employee monitoring solutions would be able to identify when user behaviors are moving critical data and especially if they are unauthorized to do so. 

2. Protecting Networking Vulnerabilities

Mobile devices, removable media, cloud accounts, third-party partners, and personal networks are a business’ biggest vulnerabilities. WIth DLP software in place, companies can have better oversight on each of these vulnerabilities, as well as on networking movements. 

By classifying these network access points and organizing sensitive data in secure locations, known and unknown vulnerabilities will be better monitored and controlled. 

3. Sensitive Data Discovery and Classification

Many businesses do not even recognize the range of confidential data that they have on their systems. Therefore, DLP aids in data discovery, finding data in forgotten places or areas no longer in use, and either removing data or organizing and classifying the data for rule-based alerts. 

4. Data Compliance

Businesses that collect data usually have to abide by compliance. Sensitive data must be kept on PCI-SSD hardware, encrypted, and protected based on other compliance regulations. 

Therefore, DLP security can immediately recognize certain classifications and set rules for these data points. Or, an organizational security team can categorize data and alerts can be customized based on their compliance needs. 

5. Protection Against Malicious Attacks or Stolen Data

Malicious attackers can cause a data breach and gain entry into a corporate network in a myriad of ways

DLP solutions are set up to be the next line of defense when malicious attacks are in your network. Keep an eye on the data that matters so that a data leak occurs, either due to stolen or leveraged by malicious actors.

6. Centrally Managed Sensitive Data

Managing sensitive data can be tedious, especially since different data types can be in multiple locations and there are a lot of data points to be monitored. 

Therefore, the DLP tool allows system administrators to access this information in one spot, keeping monitoring more straightforward and effective.

Setting up DLP Solutions for Your Business

DLP system solutions are necessary for almost every business. If you want to implement a DLP program, you’ll need to identify the types of data that your company collects, the locations they are held, and the compliance needs that follow. Discovery software can do this for you. 
Then employ a data monitoring solution. This monitoring solution should be in addition to IP security software like firewall, antivirus, and antimalware software. Employ SIEM systems for data alerts and employee monitoring for insider threats. While there is a range of data loss prevention methods needed, this is what it takes to stay up to date on data monitoring, keep your company protected, and stay compliant around data collection.

By SoftActivity Team

May 27th, 2021