Advanced Computing in the Age of AI | Wednesday, August 17, 2022

Shift to AI Tools Doesn’t Guarantee Secure IT 

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AI and machine learning tools enlisted to bolster the security of enterprise infrastructure are ubiquitous. Still, a vendor survey reveals a persistent gap between deployment and working knowledge about the capabilities of automated security tools.

So far, the results have been mixed. An annual threat assessment released by cybersecurity specialist Webroot reveals that expanding use of AI tools to defend infrastructure is accompanied by general confusion about how best to apply the technologies.

“Despite the increase in adoption rates for these technologies, more
than half of IT decision-makers admitted they do not fully understand
the benefits of these tools,” the survey concludes. Continuing trends include “confusion and lack of knowledge regarding the use cases and capabilities of AI and machine learning-based cybersecurity tools, as well as a general distrust in their capabilities, based on how such tools are advertised by vendors,” the authors added.

Nevertheless, 96 percent of the IT managers surveyed said they are using AI and machine learning to beef up cybersecurity. Most plan to use more in 2020 as security threats proliferate and evolve.

TheWebroot study was completed before the COVID-19 pandemic spread to Europe and North America. Since then, security experts have warned of additional enterprise security threats as most employees work from home.

For example, the International Association of IT Asset Managers warned on March 27 that companies will encounter a “huge data control problem” as they face their first major billing cycle since offices were shuttered due to the coronavirus.

“This opens up the potential for breaches and fraud on a scale never before seen,” warned Barbara Rembiesa, the association’s president and CEO.

While the vast majority of respondents to the Webroot poll said they research and seek out automated security schemes, 70 percent said they’ve been hit with a “damaging” cyberattack over the last year despite using AI- and ML-based tools. Those contrasting stats suggest automation goes only so far when defending critical IT infrastructure.

Threat alerts and detection were the top uses cases for AI-based security tools, followed by automated network analysis and spotting threat patterns. Top reasons for failure to detect and stop attacks included lack of training with new AI tools, overpromising by cybersecurity vendors and plain-old employee negligence. Improper installation and configuration of automated security tools was also cited.

“Realistically, we can’t expect to stop sophisticated attacks if more than half of IT decision makers don’t understand AI/ML-based cybersecurity tools,” said Hal Lonas, CTO of Webroot’s parent company, OpenText Corp. (NASDAQ: OTEX). “That means more training and more emphasis not only on our tools and their capabilities, but also on our teams’ ability to use them to their best advantage.”

The Webroot security survey was conducted between Nov. 15 and Dec. 3, 2019, and includes responses from 800 IT managers in the U.S., U.K., Japan and Australia.

About the author: George Leopold

George Leopold has written about science and technology for more than 30 years, focusing on electronics and aerospace technology. He previously served as executive editor of Electronic Engineering Times. Leopold is the author of "Calculated Risk: The Supersonic Life and Times of Gus Grissom" (Purdue University Press, 2016).

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