Dlp is the acronym that is used to indicate the data loss preventioni.e. the prevention of corporate data loss
It consists of the set of software tools that are used to prevent users from spreading outside the corporate network sensitive information: system administrators, in particular, have the ability to check which data users are entitled to transfer. Depending on company rules, data loss prevention tools can be calibrated differently, but the purpose is always the same: to ensure that confidential information is classified and protected. Therefore, users cannot expose data that could compromise the security of the organization, whether this happens intentionally or accidentally.
A concrete example
Consider, for example, an employee trying to forward a email message: well, in such a situation some security measures may come into operation, by virtue of which the employee will not be able to continue with his intent or will at least receive an alert to confirm the sending. The same can happen in the event that a worker tries to upload a file to your personal account by Dropbox.
The fight against threats
The damages that can result from data loss are manifold, and it is for this reason that organizations are resorting to a wide range of dlp tools: the intent is both to comply with the prescriptions deriving from the laws concerning data privacy, which are increasingly restrictive and impose access control for a optimal data protection, and to protect oneself against threats that can come directly from within companies. There are data loss prevention tools that allow you to control the activities performed by corporate devices and computers, but also to protect sensitive data and filter the data flows that cross corporate networks.
The data classification depending on the context it is an appreciable approach for its simplicity and from the point of view of scalability. In practice, it is a question of attributing a specific classification to the users who created the data, to the storage devices or to the applications. As these classification labels are applied to data, companies have the opportunity to monitor how it is used. At the same time it is very important content inspection: it involves analyzing data in order to identify specific formats (for example keywords such as “confidential”, document codes and credit card numbers).
The necessary checks
In the context of dlp collaboration between the managers of different departments, in order to understand why some data is out there. Thus it is possible to study and implement the various controls that are essential to limit the risk of compromise. In the context of a dlp plan, the checks relating to the methods of using the data are quite simple and concern, among other things, the monitoring of behaviors that are considered to be at risk. The subsequent development of the data loss prevention strategy allows you to develop increasingly precise and targeted control policies: the result is a granular monitoring that allows you to contain all risks.
For all companies, small or large, data represent a very important asset of absolute value. It is therefore not difficult to guess the extent of the damage that may result, both legally and economically, from the loss of such significant information. Day after day the data is collected, examined and used in order to develop the various business plans. The concept of data loss indicates the organization data loss which can occur due to an external attack or an incident, such as a problem on corporate devices or software in the absence of an adequate backup. It is necessary to distinguish the data loss from the data breach (which pertains to unauthorized access by cyber criminals to sensitive data) and from data leak (which consists, instead, in the unintentional exposure of sensitive data on physical devices or on the web).
What are dlp systems for
It must be said, however, that i dlp systems they are able to prevent not only data losses, but also data breaches and data leaks, enabling organizations to ensure the highest standards of protection and at the same time reduce IT risks. The classification of data requires first of all to identify their typology, and then identify potential threats and evaluate the impacts that could derive from the loss of data, also according to the various degrees of confidentiality that characterize them.