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What is Data Loss Prevention (DLP)? (Types, Importance, How Does It Work?
<p>Data Loss Prevention (DLP) refers to the cybersecurity measures and safeguards that individuals and corporations employ to prevent and identify data loss on their networks, whether as a consequence of data breaches, malware attacks, or other means. While ordinary Internet users should be interested in DLP to safeguard their personal data and devices, corporations are investing in DLP to secure their data in accordance with government laws.</p><p>DLP technologies perform both content inspection and contextual analysis of data sent via messaging applications like email and instant messaging, in motion over the network, in use on a managed endpoint device, and at rest in on-premises file servers or in cloud applications and cloud storage. These solutions respond depending on the policies and guidelines set in place to mitigate the risk of unintended or accidental data breaches or sensitive data exposure outside of approved channels.</p><p>DLP is frequently mixed up with <em>data leakage prevention</em>, which is similar but differs significantly. The methods used by corporations to avoid data security breaches are known as data leakage prevention.</p><ul class="list"><li><p>When sensitive information leaves an organization and ends up in the hands of a third party, this is known as <em>data leakage</em>.</p></li><li><p>Data loss, on the contrary, occurs when data is lost by accident or taken by a cybercriminal on purpose.</p></li></ul><h2>Why Do Companies Use DLP?</h2><p>The goal of Data Loss Prevention is to prevent data from being transferred outside of a business. DLP is commonly used by businesses to −</p><ul class="list"><li><p>Protect Personally Identifiable Information (PII) and follow all applicable laws.</p></li><li><p>DLP can help organizations protect their intellectual property.</p></li><li><p>DLP can help achieve data visibility in big organizations.</p></li><li><p>In BYOD (Bring Your Own Device) situations, DLP can secure your mobile workforce and enforce security.</p></li><li><p>DLP can secure the data on cloud systems from afar.</p></li></ul><h2>How Does DLP Work?</h2><p>To fully understand any DLP solution, you must first understand the distinctions between content awareness and contextual analysis. If the content is a letter, the context is the envelope, which is a good way to think about the distinction.</p><p>While content awareness entails grabbing the envelope and gazing inside to study the contents, context entails exterior characteristics such as the letter's header, size, format, and other elements that aren't related to the letter's content. Although we want to use context to get additional intelligence about the material, the notion behind content awareness is that we don't want to be limited to a particular context.</p><p><strong>Types of DLP</strong></p><p>There are two types of DLP −</p><ul class="list"><li><p><strong>Enterprise DLP</strong> − It is a specialized, complete, stand-alone solution that answers today's enterprise's complicated demands. To monitor email and networks, Enterprise DLP is packaged as software for servers, workstations, and virtual appliances.</p></li><li><p><strong>Integrated DLP</strong> − It is a more straightforward solution that integrates with existing cybersecurity solutions. Integrated DLP focuses on enforcing regulations, ensuring compliance, and preventing unauthorized individuals from accessing particular digital assets. Secure online gateways, secure email gateways, business content management systems, and different data categorization and discovery tools are the only places where integrated DLP is implemented.</p></li></ul><p>DLP is a basic set of guidelines that involves identifying sensitive data that must be secured and then preventing its loss. Data might exist in a variety of states across your infrastructure, making it difficult to identify sensitive data. Three types of data are given importance −</p><ul class="list"><li><p><em>Data that is being used</em> − Data in RAM, cache memory, or CPU registers that are now active</p></li><li><p><em>Data on the move</em> − Data is sent across a network, either an internal and secure network or the public internet.</p></li><li><p><em>Resting data</em> − Data is stored in a database, a filesystem, or a backup storage infrastructure.</p></li></ul><h2>Content Analysis Techniques Used in DLP</h2><p>There are a variety of content analysis techniques that may be used to trigger policy violations as soon as the content of the envelope is examined −</p><ul class="list"><li><p>The most popular DLP analysis approach comprises an engine evaluating information for specified rules such as 16-digit credit card numbers, 9-digit US social security numbers, and so on. Because the rules can be created and executed fast, this approach is an ideal first-pass filter, albeit it is prone to large false-positive rates without checksum checking to identify legitimate patterns.</p></li><li><p><strong>Database Fingerprinting</strong>, also known as Precise Data Matching, examines exact matches in a database dump or a live database. Although database dumps or active database connections degrade performance, organized data from databases can be exported in this manner.</p></li><li><p><strong>Exact File Matching</strong> − While the contents of files are not examined, the hashes of files are compared to exact fingerprints. Although this strategy works for files with numerous similar but not identical versions, it does not work for files with multiple similar but not identical versions.</p></li><li><p><strong>Partially Matching Documents</strong> − Looks for a complete or partial match on certain files, such as numerous copies of a form filled out by various people.</p></li><li><p><strong>Conceptual/Lexicon</strong> − These policies may warn on entirely unstructured thoughts that defy easy classification using a mix of dictionaries, rules, and other tools. It must be tailored to the DLP solution offered.</p></li><li><p><strong>Statistical Analysis</strong> − Detects policy breaches insecure material using machine learning or other statistical approaches such as Bayesian analysis. Requires a vast amount of data to scan from; the more the data, the better; otherwise, false positives and negatives are common.</p></li><li><p><strong>Pre-built categories</strong> − For typical sorts of sensitive data, such as credit card numbers/PCI protection, HIPAA, and so on, there are pre-built categories with rules and definitions.</p></li></ul><p>Your DLP system must know how to handle sensitive data after it has been recognized. You'll need to tread carefully in order to find a balance between securing your data and making your workers' duties too difficult. The DLP rules and processes you'll apply with your DLP system will be informed by your strategy. Those rules and procedures may be thought of as the technical representation of the strategy that your company creates.</p><p>Finally, if your solution detects an action that breaches one of the policies you've established, it will apply DLP security measures to avoid data loss. If your DLP solution identifies a sensitive file attached to an email, it may display a warning to the sender or even prohibit the email from being delivered. If sensitive data is being exfiltrated across the network, the DLP solution can either notify an administrator or simply disable network access.</p><h2>Importance of DLP</h2><p>Today, data loss prevention is a must-have corporate practice. Any data loss might be devastating, from health records to credit card information and individually identifying consumer information. The worrying findings of data not being sufficiently safeguarded highlight the need for DLP. The number of records exposed in 2019 was estimated to be in the billions, making it the "worst year on record" for breaches. Data protection and privacy are governed by strict international rules.</p><p><em>For individuals −</em></p><ul class="list"><li><p><em>Data protection</em> − Keeping your personal information out of the hands of hackers might help you avoid crimes like identity theft.</p></li><li><p><em>Network security</em> − DLP and network security go hand in hand. A DLP strategy can help safeguard your primary network and the devices that link to it.</p></li><li><p><em>IoT device security</em> − When IoT devices are protected by antivirus software and guest networks that help keep your data secret, they are significantly safer.</p></li></ul><p><em>For businesses</em></p><ul class="list"><li><p>Despite the fact that legislation differs by nation, state, and sector, most firms must adhere to government-imposed data protection guidelines. These guidelines govern how businesses manage and safeguard their consumers' data.</p></li><li><p><em>Intellectual property</em> − If a company's network is breached by hackers, trade secrets and business plans might be revealed to the public for all to see.</p></li><li><p><em>Data transparency</em> − A corporation must know where its data is held, who has access to it, and for what reason in order to secure it. This can aid in the detection of flaws and the avoidance of avoidable risks.</p></li></ul>
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