Data Protection our series on the basics of information security, and how to develop data loss prevention strategies, including best practices and strategies.
The policy related to Data loss prevention should be based on how organizations can share and protect their data. This explains how data can be used in decision making without being accessed by anyone who is not authorized to access it.
Prevention of data loss is generally defined as a technology or process that:
- Identification of confidential data
- Track data usage
- Avoid unauthorized access to data.
- Software products that can classify and protect data.
Why Data Loss Prevention Policy is Important?
Most data security involves preventing attacks on the organization’s network. Employees have more ways to access organizational data compared to earlier days, and that is due to the nature of modern distributed computing. The chances of accidental loss of data are high here, and it can be a serious problem.
Data storage in the cloud and on remote sites. This becomes a serious issue, because the number of employees working remotely increases, the frequency of access to confidential data from laptops and potentially vulnerable mobile devices also increases.
Data collection and use are subject to improved regulatory controls. Data loss prevention policies are based on three main reasons:
- Compliance: Data loss prevention policy is an important element of regulatory compliance with data and reporting of compliance audit information. The government has several levels of regulations about how organizations collect and obtain personally identifiable information.
- Intellectual Property: Confidential Information and Trade Secrets are the types of information that must be protected from unauthorized access.
- Data visibility: Organizations can obtain valuable information by controlling the way stakeholders’ access and interact with data.
Data Loss Prevention Policy and Best Practices
A data loss prevention policy can help organizations prevent unauthorized access to data and protection from potential damage. Although no protection is bulletproof, there are a number of recommendations that can help you develop an effective data protection policy:
- Identify the data that the organization intends to protect. Since most often data is classified based on the risk factor and their vulnerability and risk factors, it is better to understand and classify data in advance. This will lead to a better understanding of the organization.
- Establish criteria for evaluating data loss prevention providers. Choosing solutions to prevent data loss can be intimidating. However, creating a rating system with the right questions can help you make an informed purchasing decision.
- Clearly define the roles of those involved in preventing data loss. It is not only about who will control the use of data and set the rules. Segregating duties helps prevent abuse.
- At first, everything should be easy. Choose a data type or a specific risk to deal with. The goal is to ensure the security of the most important data, quickly win a tangible victory and develop it.
- Get the support of your organization. Each department or unit head plays a role in determining the data loss prevention policy appropriate to the corporate culture. This strategy applies to all departments and functions.
- Brief all company employees how and why the Data Loss Prevention Policy applies. Many managers consider employees to be the weakest link in data loss prevention, but they do not consider security training a priority.
- Carefully document data loss prevention processes. The written policy should focus on protecting data.
- Monitor data usage before blocking it. Configure data loss prevention to first signal the loss of sensitive data. Make sure that the rules that block data transfer will not disrupt the workflow.
General Inclusion in the Policies of Data Loss Prevention
A number of data privacy laws already exist, not to mention the many pending legal requirements and potential laws that are being developed throughout the world. The typical DLP strategy contains three elements:
Action: If the situation meets the conditions specified, the action is taken to avoid losses.
- Location: where the specified policy will apply
- Condition: In fact, parameters are sought by strategies to avoid data loss.
- Example: A DLP policy is configured to detect information protected by GDPR. The location will be where personal information is stored.
Conditions can include:
- Data is not used as agreed by the user.
- Old data to be deleted to maintain compliance.
- Personal data are stored elsewhere that is not protected.