Many corporations that lack adequate data loss prevention solutions struggle to keep track of all their data. One of the reasons is – employees transfer data across many communication routes, both authorized and unofficial. It causes a lack of awareness into what data is leaving the company and hampers data loss prevention.
6 Best Practices For DLP
A program that incorporates best practices for data loss protection can assist prevent confidential information from slipping into the hands of the wrong people. The best practices for data loss prevention listed below will assist you in protecting your sensitive data from both internal and external threats:
1. Identify And Classify Confidential Information.
To successfully preserve data, you must first understand what sorts of data you have. Data discovery technology will search your datasets and reflect on the findings, providing visibility into what material needs to be protected. It enables you to limit user data availability and avoid keeping sensitive data in unsecured locations, lowering the risk of data breaches and loss.
2. Establish A Comprehensive DLP Program.
Many companies use uneven, ad hoc DLP technology by diverse departments and business units. This mismatch results in a lack of insight into data resources and inadequate data security. Furthermore, employees tend to disregard department DLP initiatives and continue using data in an unprotected manner.
3. Encrypt Your Information.
All sensitive corporate data, whether at rest or in transit, should be encrypted. If handheld devices are storing sensitive data, encrypted disk technologies must be used. Encrypting the hard disks of computers and laptops will help prevent the loss of essential information even if the device is compromised.
4. Establish Incident Response And Recovery.
Corporate DLP is a program, not just a tool. Poor incident management is a major flaw in many DLP implementations. It is not uncommon for a company to go through the planning process, buy the software, and fail incident handling. Before moving ahead with the installation, make sure there is an incident response strategy and system in place.
5. Implement Anomaly Detection
Some advanced DLP technologies complement statistical correlation and regression rules with deep learning and web analytics to detect anomalous user activity. Creating a model of each user’s and a group of users’ behavior allows for precise identification of questionable conduct resulting in data loss.
6. Train Your Team
DLP relies heavily on employee understanding and adoption of security rules and regulations. Classes, online training, frequent emails, and posters can improve employee comprehension of the necessity of data security and their skills to integrate suggested DLP best practices.
A well-planned DLP solution and implementation are critical to the success of a DLP system. Your DLP approach will lead to the formation of a productive outcome that will offer governance around data security for your business now and in the future if you recognize the fundamentals and features of DLP.