List of data loss prevention examples. How much data does your company lose every year due to employee negligence or malicious attacks?
Top Data Loss Prevention Examples
Companies spend a lot of money on DLP software solutions, but often the results are disappointing. The reason is that DLP software must operate in the context of an existing information security environment. Security awareness training is an important part of that environment and is often overlooked.
Data Loss Prevention (DLP) refers to the preventive or detective controls used to monitor, control, or prevent data leakage. It involves a combination of hardware, software, and people to identify potential data leaks and prevent them from happening. DLP solutions vary depending upon the type of data being protected and who it is being shared with.
The DLP rules and policies can vary from company to company since there is no industry standard for detecting different types of sensitive information. For example, a bank will be more concerned about financial data than a clothing store will be, so their DLP policies may differ. The level of sensitivity may also depend on the region where the company operates since privacy laws vary depending on the country.
DLP Technology Communications Monitoring
Some companies are implementing DLP technology to monitor communications inside their organizations. This includes outbound traffic to detect sensitive information leaving their systems.
In these cases, the DLP system is closely integrated with other enterprise security systems.
Entity-based DLP systems work by identifying entities such as email addresses, IP addresses, files, and users. These systems monitor all communications and transactions for an entity to search for sensitive information. As new entities are added to the DLP system, the rules governing them are automatically updated to cover their characteristics.
This type of protection is useful for protecting data that can be identified by a specific person, place, or thing. However, this approach can be problematic if the same person uses multiple email addresses or if multiple people access the same computer. Also, if the same information is contained in multiple files this approach will not detect it.
Rule-based DLP Systems
Rule-based DLP systems work by identifying specific types of information and looking for them anywhere on the network. These systems look at the content of files to decide how sensitive they are and make decisions based on that analysis. This method is highly flexible but less effective than entity-based methods since it cannot detect new types of information.
The most effective data loss prevention solutions combine rules-based and entity-based approaches. Since neither approach alone can handle every possible situation. For example, a rule-based system could look for credit card numbers in files.
But then an entity-based system could look for subsequent transactions using those numbers. That is to prevent fraud and detect leakage of sensitive information to unauthorized people or organizations.
DLP Overview
The purpose of DLP systems is to help protect sensitive information from leaving the network where it can be accessed by unauthorized people. One of the primary challenges for DLP systems is to find new ways to protect data as security threats evolve. For example, encryption protects data while it is in transit.
It can’t protect data at rest on a network server or in a laptop that has been stolen. Therefore, DLP solutions must monitor outbound traffic as well as inbound traffic. Another challenge is to determine which information or actions are sensitive enough to warrant protection.