10th May, 2022
Data loss prevention is one of the vital strategies that can prevent your sensitive information from getting leaked online. You need to understand the ins and outs of DLP to implement the strategies in your existing business ecosystem.
With the rapid increase in the digital ecosystem, the surge in cyberattacks has resulted in millions of dollars lost for businesses globally.
Organizations are looking to strengthen their protection for critical and sensitive information on their network from getting breached or leaked in public.
That’s where Data Loss Prevention DLP comes into the picture.
It’s a strategy to prevent potential data breaches by detecting, monitoring, and blocking sensitive data. A dedicated DLP software is responsible for strengthening your security shield and preventing your business networks from external intrusions.
But that’s not it. Let’s dive into the nitty-gritty about data loss prevention and understand what it is and how it works to ensure robust security for your organization.
DLP is broadly categorized into three types, and different types of DLP solutions serve different purposes and deliver a quality data loss prevention environment.
The network DLP solution is delivered on the hardware or software platforms and is integrated with the different data points on your organization's network.
It monitors and delivers detailed reports of the data in transit available on the network and can scan the content passing through the organization's network.
The network DLP solution can help you get a bird’s view of what data is used, who accessed it, and where it is channeled. All the information is stored in a secure database that can be accessed easily.
Storage DLP enables you to have centralized access to the information like what data your employees share and store and the confidentiality of the information shared on your network.
You can view confidential files shared and stored by people accessing your corporate network and help you prevent data leaks and identify sensitive points. If your data is stored on the cloud network, storage DLP helps you control the data shared on the network.
Endpoint DLP solutions help prevent data loss because of removable devices like pen drives or others. Multiple external tools can quickly transfer data and put your organization's security at high risk.
To avoid international or accidental data leaks, endpoint DLP is installed on the workstations and multiple devices on your company network to prevent the outward flow of vital data by clipboards, sharing applications, or removable devices.
Now that we understand the types and the purpose of different DLP let's dig deeper and understand how DLP systems work.
A DLP uses different security measures like antivirus software, endpoint protection tools, firewalls, monitoring services, artificial intelligence, and machine learning to help you prevent data breaches and other unwanted activity in the organization's network.
The DLP is supported by one or multiple cybersecurity activities like
Prevention: A real-time data stream review is established to restrict unauthorized users or suspicious activities.
Detection: Improved data visibility and advanced data monitoring can help to spot anomalous activities that can harm the organizational system.
Response: Reporting and tracking data access and other movements on the enterprise network can help to streamline incident response.
Analysis: Strengthening the preventive measure for network high-risk or information remediation activities.
If we boil it down, DLP solutions identify or spot the sensitive data that requires protection and prevent it. But different states in your organization's infrastructure make it difficult to identify sensitive data and protect it.
The DLP solution needs to focus on different data states like:
Data in use: The data stored in the CPU registers, cache memory, and RAM.
Data in motion: The data transmitted from the internal to the public network or vice versa.
Data in rest: The data stored in the database, backup storage infrastructure, or on a filesystem.
If the DLP solution focuses on just one of the above-listed data states, it is termed an integrated DLP solution. The solutions are limited to secure web gateways (SWGs), secure email gateways (SEGs), enterprise content management platforms (ECM), data discovery tools, data classification tools, cloud access security brokers, and email encryption products.
For example, let's consider Microsoft's Exchange Server. It has the capabilities to prevent data loss via email and doesn't focus on other data states.
And if the focus is spread across all the states, it’s called an enterprise DLP solution. The solutions are extensive and packaged in software for desktops and servers, soft appliances for data recovery, or physical or virtual appliances for focusing on networks.
DLP solutions use an agent program to sniff through different data states and spot the worthy sensitive data that requires protection. These programs use different DLP techniques to perform the desired actions.
Let’s go through the details of those techniques used by agent programs to scan and spot sensitive data in different data states.
Out of multiple techniques used in the DLP solutions, we have shortlisted the top to help you understand the core operation of analyzing policy violations and spotting sensitive data for robust protection.
Rule-based analysis: One of the most common techniques used in DLP focuses on analyzing content on specific rules like 16-digit card numbers, 9-digital social security numbers, etc.
These rules can help you quickly process and configure sensitive data and increase valid pattern recognition. The technique is an excellent first-pass filter but is prone to false-positive rates that can decrease the reliability of the technique.
Database Fingerprinting: It is another powerful technique that helps analyze vital data available in different states of the organization's ecosystem. Also known as exact data matching, the technique focuses on spotting the exact matches from the live database or database dump.
You can use the mechanism to scan through structured data from the database as the live database and database dum connections can affect the performance.
File matching: File matching consists of matching the hashes of the file against the exact fingerprints. It doesn't involve matching the exact file, resulting in a long and tedious process. The technique has a comparatively low false-positive rate than the other techniques, but the approach can fail in the case of almost similar files with different versions.
Partial matching of documents: The technique focuses on matching partial or complete versions of specific files to sniff the sensitive data and protect it using different techniques. In the case of forms that different users fill, this technique can work great and deliver the best results for the DLP solution.
Lexicon/conceptual: A combination of rules, dictionaries, etc., can alert different unstructured ideas that defy simple categorization. The data needs to be categorized and sorted for the DLP solutions to execute and deliver results.
Analysis based on stats: Using statistical methods like Bayesian analysis and machine learning to spot the data that needs protection and is sensitive is a practical approach for providing a DLP solution.
It requires a broad volume of data to be scanned to avoid false positives or negatives. If a small data volume is used, it decreases the technique's efficiency and compromises security.
Pre-built categories: There are some pre-built categories with dictionaries and rules for multiple common types of essential data like PCI protection/credit card numbers, HIPAA, etc. It increases the technique's efficiency and helps to spot the data easily.
Apart from these, there are numerous techniques in the industry that aim to deliver different data inspections. Some DLP vendors have customized engines to scan the data states, and others hire third-party technology to solve their security concerns.
The increased reliability of business toward cloud services has increased the necessity of DLP solutions, and data protection should be organizations' primary focus.
Over 18.1% of the uploaded file-sharing data on the cloud contain confidential information like protected health information (PHI), personally identifiable information (PII), intellectual property, or payment card data.
You need to deploy the right DLP solutions that deliver an analysis of data in motion, real-time monitoring, accuracy, incident remediation, and different data loss policies that strengthen the security of your sensitive data.
Now that you are aware of the brief of DLP solutions and how it works, it's time to take some action.
Now that you know different types of DLPs, and how it works, you have taken the first step towards implementing robust DLP security solutions to prevent sensitive data breach on your business network.
To implement DLP solutions, you need to analyze different business security requirements and point out the roadblocks and security loopholes.
Analyzing different data states with different techniques in the DLP solutions can help you monitor and shield your enterprise's essential data from being leaked publicly or exploited by hackers or unwanted intrusions.