With AI, companies can now secure the millions of files and documents their users create and manage every day. Accurate and automated unstructured data security is here! Karthik Krishnan, Co-founder and CEO at Concentric AI explains how enterprises need to leverage it.
Zero-trust and least-privileges access – two of cybersecurity’s most useful frameworks – are also relevant for unstructured data security. But both approaches are typically thought of in terms of the network. Now, with new AI capabilities, zero-trust and least-privileges access solutions are also available for the millions of files and documents users create and manage every day.
Knowing What You Have
Unstructured data is fantastically complex and diverse as seen in this study. Specialized data, such as a contract or a sales strategy, might be both strategically valuable and difficult for outsiders to understand – unlike a discrete networked resource that often has a fairly high IT profile, is well-understood, and is “worthy” of attention and resources.
Attempts to “scale” security to unstructured data have, so far, been time and labor sinks. Pattern matching and end-user file markup techniques are two common approaches. Neither option is working very well.
Knowing What to Do
For the same reasons, developing policies for networked resources, while not easy, is at least manageable. Unstructured data is different. It’s diverse and dynamic, changing with time and business imperatives. Data loss prevention (DLP) technologies take a stab at the unstructured data policy problem, but DLP implementations are highly complex beasts bordering on unmanageable.
Knowing what policies to apply to each file is a very tough problem, and so far it hasn’t scaled well at all.
Zero Trust / Least Privileges with Deep Learning
These two problems – discovering/categorizing your data and defining appropriate access policies – are now solvable with automated deep learning solutions.
Deep learning reveals document meaning and context to provide accurate, granular categories that reflect business criticality. These categories are essential for zero-trust security solutions. Deep learning, being far more accurate than pattern-matching and far easier to implement than end-user classification programs, is the answer.
Once categorized, deep learning can establish a security baseline for each category. That baseline encompasses how files are permissioned, shared, stored and managed, and it reflects the policy decisions made by the people who know those files best – the owners and end-users. From here it’s an easy step to narrow file access to only those needing it – automatically and accurately.
Zero trust / least-privilege security is possible for unstructured data. Using AI, by categorizing data and discovering the most appropriate security policies for each file, we’ve kicked away the barriers to effective, efficient and focused security at the file level. We’re finally ready to apply two of the decade’s most powerful security frameworks to the spreadsheets, reports, presentations and other documents that, until now, have been beyond the security team’s reach.
