Cyber Defense eMagazine March Edition for 2022

modern work. Organizations must be ready to navigate this apparent paradox to get the most out of their
data while minimizing the risk.
The Two Faces of Enterprise Data
An organization’s data and secrets are simultaneously its greatest assets and its greatest risks. On its
good side, data is the oxygen that keeps the enterprise alive and lets it thrive. And like oxygen, data
needs to move and be consumed so that users can collaborate and create. And today this sharing occurs
across a constantly evolving suite of applications and services including sanctioned enterprise apps as
well as personal use apps.
Yet all this sharing and collaboration opens the door to loss, misuse, or abuse of that data and can
transform data from Jekyll to Hyde. Viewed from the perspective of risk, data is less of a life-giving oxygen
and more like a self-spreading, self-replicating virus. Every user that downloads sensitive data could
potentially make a copy. Data could be copy/pasted into another file, uploaded to a personal cloud, or
shared via chat, personal email, or countless other methods. Every data access can turn into a number
of unseen derivatives, each with its own potential for loss or misuse.
Focus on the Data Actions
So which is it? Is our data oxygen or a toxic virus? The answer is that it is both. The difference between
data being nourishing or toxic depends on the actions and context surrounding it. The good or bad rests
in how the data moves, is modified, and shared. Just as importantly, we need to know the data’s history.
Where did the data come from? What user or app created it and how has it changed? So not only do we
need to know the actions surrounding a piece of data, we need to know its lineage.
The Way Forward
Organizations need a new approach to data security that can provide this lineage and resolve the Jekyll
and Hyde problem by passively watching how data is created, modified, and shared. Every action must
be tracked and correlated to build a complete history of every piece of data. This opens up a far more
powerful approach to securing data that lets organizations do the following:
• Secure Any Type of Data - Any data can be traced and analyzed without the need for signatures
or tagging. This lets organizations protect virtually any type of IP or content based on its actual
value to the enterprise. Source code, ML models, financial projections, and product designs can
all easily be protected equally.
• Safely Enable Work and Collaboration - Users need to share and collaborate to do work without
losing control. Policies can align with business processes to define how data can be shared and
with whom while preventing oversharing or misuse.
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