Over the past weeks, the discovery of classified documents in the homes of current, and past, top U.S. government officials really brings home the reality that classification of proprietary, confidential information is deeply flawed. These recent events have experts saying that the practice of the U.S. government classifying tens of millions of documents a year is excessive and that there are, in fact, several potential dangers to over-classification. What’s more, these events also validate that data – whether paper or electronic – will find a way to flow outside of your trusted locations. It really doesn’t matter if it’s intentional or accidental. The question is: when will you find out? And what might be the damage?
Data loss prevention (DLP) technologies have become synonymous with data loss prevention strategies – despite the fact DLP technologies are often challenged by complexity and ineffective implementations. What’s the reason so many organizations stop short of implementing robust data loss prevention strategies, instead simply relying heavily on DLP technology to do the work? One big reason: classifying data is a massive challenge. Layer on top of that keeping up with policies, exceptions and rules and you end up having either frustrated employees or frustrated security analysts – or both. A few years ago, Code42 nailed this sentiment with the slogan “I love my DLP…said no one ever.” More recently (and more seriously), leading analysts have highlighted that “organizations struggle” with DLP and that existing technologies have created “stakeholder frustration.”
The reality is, the way we work (and behave) today – with speed, distractions, and a plethora of methods and apps to move, delete and change data – is driving companies to demand a new way to solve for data loss from insiders. And it’s driving Code42 to continuously innovate around the programs, processes and technologies needed to solve for this massive challenge.
Implementing an effective data loss prevention program is much easier than it was twenty years ago, and much faster too. But it can’t be done with the tech of old.
Here are the seven requirements you should consider when evaluating technologies for the modern day
- Architecture: Lightweight agent, API cloud coverage, SaaS-based with workloads in the cloud
- Cross-platform: Ability to work across Mac, Windows and Linux and regardless of Office Suite (Microsoft, Google)
- Complete visibility: to all data sources, types and destinations – without reliance on classification, tagging and policy management
- Fidelity: data correlation using file, user and destination context to transparently prioritize risk and o expedite investigations
- Proportional response: Support for robust response controls ranging from education, to containment, to prevention in order to effectively protect data while balancing security and employee workloads
- Integrated: Ability to easily integrate with your IAM, PAM, SIEM, SOAR, HRIS and other systems to streamline workflows and extend your tech stack
- Fast and easy to use: Can be up and running to deliver value in weeks, not months, without adding an FTE
So in the end, you want to know – with certainty – if there’s a there there. And you can. Just not with old school classification. And not with legacy DLP technology.
Contact us today for a demo or to see Incydr in action in your environment.