We are the Borg. You will be assimilated. Resistance is futile.
Organizations today find themselves in a situation not unlike that of the Enterprise crew in “Star Trek.” They are facing a formidable, technologically advanced enemy capable of taking over key components of the organization. In one episode of “Star Trek,” in fact, the Borg collective takes control of Captain Jean-Luc Picard himself, to the horror of his crew.
Cognitive Security Fills In Critical Gaps
So how can organizations fight an enemy of great patience and persistence, capable of launching surgically targeted attacks and assimilating systems and people into its own collective? Machine learning is our best hope.
Machine learning is our best hope to help incident responders, security analysts and, ultimately, security leaders restore a sense of balance, a sense of peace in the universe. When the time to discover an intrusion is measured in months or years; when the people responsible for keeping track of threat vectors can’t keep up; when the incident responders can’t determine quickly and accurately enough whether an alert is a benign event or the tip of the iceberg for what could be a jaw-dropping cyber incident … where can you turn?
“Star Trek,” of course. And when you’re done binge-watching all the episodes, you can start looking into the progress that has been made in cognitive security — the application of artificial intelligence and machine learning concepts to the cybersecurity battlefront.
A recent report by IBM’s Institute for Business Value (IBV), based on a survey of 700 security leaders back here on Earth, revealed that IT teams are looking for ways to more effectively address three main shortcomings in their security response capabilities: a speed gap, an accuracy gap and an intelligence gap.
Resistance Is Futile Without Machine Learning
According to the survey, most security leaders have high hopes for cognitive security, though there will certainly be some resistance — most likely from the same folks who resisted the move to the cloud, or those who try to argue that their organizations should steer clear of investments in Internet of Things (IoT) projects.
But even this resistance will be overcome — but not by the Borg. It will be overcome by pressure from competitors, pressure from the marketplace or pressure from top leadership. Yes, machine learning can be scary; I fully realize the weight of these words knowing that in the very near future, such an intelligence might be reading this very article, processing its words, absorbing its points and counterpoints and perhaps even making sense of my analogies. However, without the assistance of cognitive computing, I don’t see a way for us to level the cybersecurity playing field.
We have no choice but to boldly go where no human has gone before — to trust artificial intelligence.
Read the full IBM report on Cybersecurity in the cognitive era
InfoSec, Risk, and Privacy Strategist - Minnesota State University, Mankato
Chris Veltsos is a professor in the Department of Computer Information Science at Minnesota State University, Mankato where he regularly teaches Information ...