Manufacturers of Data Loss Prevention software create their products to assist businesses in establishing rules around what employees are permitted to do with data. The underlying idea behind this software—creating policies, categorising data, and preventing particular actions—hasn't altered since it was first developed about thirty years ago. The principles of classic Data Loss Prevention are reasonable in theory, but they are impractical in the cloud-first world of today.
Data Loss Prevention are no longer as effective as they were were for three main reasons:
· Data labelling is difficult—almost impossible. Effectively implementing data labelling regulations or upholding precise asset tagging at scale is practically impossible. Today, too much digital work has been produced, and every employee has access to it.
· Bad user behaviour may result from complex data regulations. Employees who simply want to complete their tasks will frequently manipulate the system, dodge rigorous restrictions, or purposefully misclassify data.
· All data movement is not monitored by legacy Data Loss Prevention. Only tagged data is monitored by DLP vendors, creating a compartmentalised view of data transit that may be blind to dangerous behaviour.
Consider developing policies that take into account all data in the cloud environment and concentrate on protecting data rather than preventing loss in order to avoid creating an unsuccessful DLP strategy.
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