User Behavior Analytics (UBA) is a method of analyzing human behavior in business operations to safeguard against potential threats. It’s one of many tools in a security team’s toolset. UBA is a powerful way to detect abnormal behavior and potential security risks, including insider threats and cyberattacks. UBA is an excellent method to mitigating the loss of a company's high-value assets, but it has not yet lived up to its promise or full potential.
Transparency, reliability, and accessibility have been some of UBA’s major pitfalls.
Transparency
Since the beginning, UBA has involved a black-box approach, in which the inner workings of algorithms used are unknown. In 2015, businesses started using analytics and automating some of the manual labor it takes to put machine learning and big data to work and coined the term “UBA.” The problem was that many folks needed months of training before they could grapple with data in meaningful ways.
Reliability
Today’s tools still take months to set up and require tedious data plumbing to “train” the black-box system and continuously maintain it, only to retrieve a lot of noise and false positives. Businesses end up with overburdened security professionals pulling logs and plumbing data instead of conducting meaningful analysis and offering critical insights and strategies to reduce risk.
Accessibility
Aside from the lack of efficiency, 80% of businesses can’t afford existing UBA tools. Only the largest companies can afford to purchase, configure and maintain this kind of software priced at tens of thousands of dollars.
UBA should be accessible to businesses of all sizes and should strive for analytics to work for you instead of having you work for analytics.
The future of analytics is bright. There is much room for improvement, and advancement in technology will allow humans and machines to communicate seamlessly. UBA will be delivered in human-understandable packages and evolve from a notoriously costly tool into one that anybody can implement and use.
Natural Language Processing Solution
Unlike traditional convoluted and slow ways of implementing UBA, natural language processing will make it much easier for humans and machines to communicate. Humans will ask machines questions in human language, and machines will communicate back in a human-readable format 24 hours after software installation. Engines will triangulate information based on questions and will let your organization know in simple terms which individuals seem rogue and why, allowing you to use human intuition and take action fast.
Check out this conversation with Fletch’s CEO and Founder, Grant Wernick, to learn about his perspective on the evolution of UBA.
If you are interested in learning more about how Fletch is solving UBA, please contact us at uba@fletch.ai or sign up for a demo on our website.
