7 Step Data Loss Prevention Checklist for 2021

Ensure the security of your organization’s sensitive data with this data loss prevention checklist, intended to help mitigate both internal and outsider threats.

For companies worldwide, it has become essential to safeguard sensitive information such as Personally Identifiable Information (PII), Protected Health Information (PHI), and customer financial information. These categories of sensitive information are protected by regulations such as the GDPR, CCPA, HIPAA, and PCI DSS. Besides these, you will also want to secure intellectual property (IP) such as trade secrets, business plans, product designs, or know-how to retain a competitive advantage.

With a  data loss prevention (DLP) strategy, it becomes much easier to ensure that your organization’s confidential information will not get exposed. If you’re just initiating a DLP program, there are some fundamental steps that you must take. The following checklist intends to provide a general framework for your DLP strategy and help you choose the right DLP solution for your company.

1. Create a data inventory

If you’re looking to create a comprehensive data loss prevention plan, then the first step is to make a data inventory. Being an essential part of data protection, the process of data inventory involves data discovery and data classification, helping organizations to understand, remediate, and manage privacy risks. Data inventory should provide detailed information about your company’s data assets, including the type of data you collect, where it is located, and with whom it is being shared. It is also crucial to analyze how sensitive data is being managed and protected and where security gaps may exist.

2. Develop a classification system 

Data classification is the process of organizing data that your organization collects into relevant categories for more efficient use and protection across company networks. It should cover both structured and unstructured data, tagging it based on its level of sensitivity and making it easier to find, track, and safeguard. Your data classification framework contributes in a significant way to risk management, data security, and regulatory compliance. 

Data security categories might include confidential and internal information, PII, financial and regulated data, public information, IP, and more. Categories should be kept simple, so all of your employees can properly apply them.  Applying persistent classification tags to data is essential and allows your organizations to track their use.

3. Identify & assess compliance obligations

Regulatory compliance has become increasingly important in the last few years. The EU’s GDPR had a ripple effect across the world, and governments are pushing for new data protection laws that protect their own data subjects and bring their legislation up-to-date with the international standard set by the GDPR. Non-compliance can have many negative impacts, including hefty fines, reputational damage, and loss of consumer trust. 

However, regulatory compliance should be just the baseline of your data loss prevention strategy, as regulations don’t cover your organization’s more nuanced data protection needs. Besides data such as PII, PHI, and your customers’ financial data protected by laws, it is also just as essential to safeguard your intellectual property, business data, and other assets that mean competitive advantage.

4. Understand when data is at risk

Understanding how data moves, how it is used, who has access to it, and how it is put at risk is critical. This step is essential for your organization in order to develop appropriate policies that can mitigate the risk of data loss while allowing appropriate data use. 

Different types of data are at risk at different times and in different ways. You need to know what actions increase the risk of data loss. This will help plan your policies in a structured way and implement them efficiently and coherently in the DLP software.

5. Set up DLP policies

There is a wide variety of data loss prevention solutions available on the market. When looking to find the best one for your organization, you need to consider your existing IT infrastructure and your specific needs.

However, the basics are the same. Any good DLP solution will allow you to discover, monitor, and protect sensitive data such as PII, PHI, and IP.  It will ensure the safety of both data in motion on the network and the data at rest in storage areas or on desktops, laptops, etc. DLP solutions also detect data use policy violations and offer remediation actions. Many DLPs come with predefined policies for regulations such as the GDPR and HIPAA and also allow you to create custom rules.

Suppose you have multiple operating systems in your network. In that case, it is important to choose a cross-platform DLP that ensures the same level of protection regardless if it is a Windows, macOS, or Linux endpoint.

6. Educate your employees

User training can efficiently decrease the risk of accidental data loss by insiders. Employees should be aware of the importance of data loss prevention and your company’s security policies. This step should be a continuous reinforcement rather than a one-time event. 

Your organization should have documented data loss prevention policies and processes and provide your employees with the information they need to understand their responsibilities. Advanced DLP solutions also offer user prompting when employees violate a company policy.

7. Monitor and improve

Your data loss prevention program should be an ongoing process. You can start this process with your most critical data, and expand it over time. In this way, you can ensure minimal disruption to your business processes. You should also monitor and measure the efficiency of your DLP strategy to ensure that it works as expected and to detect gaps.

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