What is Data Loss Prevention?
Data loss prevention (DLP) combines policies, procedures and technologies to prevent users in a network from leaking or misusing critical data while it is in use, in motion, or at rest. DLP software categorizes sensitive versus insensitive data in order to respond to potential exfiltration activities.
Benefits of DLP Solutions
Data loss prevention has been a key priority for many organizations due to the rise of insider threats, data leaks, and the passing of more rigorous privacy laws in recent years.
The main benefits of DLP solutions:
- Prevent end users from accidentally or maliciously misusing data
- Meet compliance and regulatory standards
- Monitor critical file movement
Traditional DLP software keeps a close eye on sensitive data with a complex classification system, comprised of individualized policies and tags that are assigned to each file. Typically, these solutions constantly scan for the movement of tagged files and ultimately prevent them from being accessed by unauthorized users or leaving the network.
The problem is: DLP solutions only monitor files that violate policies. This results in large blindspots when policies are written incorrectly. It also makes it difficult to protect trade secrets and other intellectual property since those files don't contain the same content patterns as regulated data.
Drawbacks of Traditional DLP Solutions
While traditional DLP sounds good in concept, most security teams describe using these solutions as "painful." Legacy DLP deployments take months or years, because proper setup requires an extensive data classification process, and refining DLP policies to fit unique users and a variety of data is complex and iterative. This complexity results in many false positives which interfere with user productivity and collaboration when it misreads acceptable employee behavior as exfiltration. In fact, 66% of companies say their DLP solutions frequently block employees from accessing data even if they are within policy.
Frustrated by these issues, business and security leaders now recognize that prevention alone is ineffective at protecting data from loss, leak and theft. Being able to detect and respond to data risk is just as important as trying to prevent it.
Areas where traditional DLP falls short:
- Data Portability. Personal cloud, removable media, bluetooth, airdrop, the list goes on but the reality is that data is more portable than ever. DLP solutions rely on blocking but users always find a way to bypass controls they feel hinder their workflows. The reality is that there are simply too many vectors to cover, not enough people to cover them, and as a result data still gets out.
- Intellectual Property Protection. Industry analysts have identified the majority of DLP use cases are focused on protecting regulated data and not intellectual property. That's because data loss prevention's narrow, rules-based focus on classification and content patterns creates blindspots when it comes to unstructured data like your trade secrets. A lack of visibility into where your product roadmaps, source code, customer lists, sales strategies, etc. live and move leaves organizations vulnerable to insider threat.
- System Complexity. DLP software takes a lot of care and feeding to keep up with the incredible amount of data that organizations create each day. Countless hours have to be spent classifying and tagging critical data--or asking users to tag their work-- to ensure everything is being monitored and blocked accordingly. Traditional DLP solutions also require on-site servers to work properly — counter to the growing business priority of moving solutions to the cloud.
Detection > Prevention
The status quo for most organizations is to try to prevent data leaking in the first place. This is ultimately what DLP software aims to accomplish.
Unfortunately, organizations are realizing that relying on prevention itself cannot work. Personal cloud, removable media, bluetooth, airdrop, the list goes on but there are simply too many vectors to cover that traditional data loss protection solutions aren't designed to handle.
A faster, simpler, more comprehensive path to data loss detection and response is the answer.
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