Data Loss Prevention (DLP) can be broadly defined as a group of technologies and practices used to protect data from unauthorized access, alteration, or destruction. In the context of enterprise security, DLP can be used to protect a company’s confidential and proprietary data from unauthorized access, alteration, or destruction.
The effectiveness of DLP can be measured in terms of the number of incidents that are prevented, the severity of the incidents that are prevented, and the cost of the incidents that are prevented. In general, the effectiveness of DLP can be enhanced by deploying data governance and data protection policies, using data discovery and data profiling technologies, and training employees on data security procedures.
One of the most common types of data that is protected by DLP is customer data. Customer data can include Personally Identifiable Information (PII), such as name, address, and Social Security number.
It can also include financial data, such as bank account numbers and credit card numbers.
DLP can also be used to protect data that is related to the company’s intellectual property. This can include data that is related to the company’s trade secrets and copyrights, as well as data that is related to the company’s patent applications.
DLP can also be used to protect data that is related to the company’s regulatory compliance. This can include data that is related to the company’s compliance with the Sarbanes-Oxley Act of 2002, the Health Insurance Portability and Accountability Act of 1996, and the Foreign Corrupt Practices Act of 1977.
DLP can also be used to protect data that is related to the company’s confidential customer information. This can include data that is related to the customer’s account history, the customer’s contact information, and the customer’s financial information.
In conclusion, data loss prevention is a valuable tool that can be used to protect a company’s confidential and proprietary data from unauthorized access, alteration, or destruction.
