Opening keynote speech at the Seattle Electrical Conference

“We can anticipate that any nation-state with a propaganda department or agency is working to right-size their capabilities to spread disinformation.” It’s especially true, he adds, among nation-states with larger budgetary allocations since they can use automation and “office employees” to distribute the narratives.

Kayne and Tom talk about the System and Communications Protection family of FedRAMP Rev5 controls. Learn about the “catch all” approach to this control family and some challenges faced to implementation. Tom and Kayne try a stout for the first time on the show, and Kayne seems to group it with all the other beers. As always, the faces he makes are impressive.

Kayne McGladrey, IEEE Senior Member, noted that the use of generative AI models in business hinges on their ability to provide accurate information. He cited as examples studies of AI models’ abilities to extract information from documents used for financial sector regulation that are frequently relied on to make investment decisions. “Right now, the best AI models get 80 percent of the questions right,” McGladrey said. “They hallucinate the other 20 percent of the time. That’s not a good sign if you think you are making investment decisions based on artificial intelligence telling you this is a great strategy four out of five times.”

We chatted with Kayne about education systems security, funding for cyber tools and services, and what the future of education might look like to fill more cyber roles.

Because of the noise-to-signal ratio, network security is particularly challenging for colleges and universities, says Kayne McGladrey, CISO and CIO of Pensar Development and member of the technology industry group IEEE.

“Every university has a whole crop of new individuals who come into the organization on an annual or quarterly basis,” McGladrey explains. With such a frequent influx of new arrivals bringing their own devices and computers, it’s essentially impossible for university IT teams to control the sheer number of new endpoints. AI can identify networking traffic, assess what “normal” looks like on a university network and do it at a larger scale that humans can accomplish. Thus, if a “faculty member normally arrives at 8 a.m., does work until 7 p.m. and then maybe logs on to her email at 9 p.m., you wouldn’t expect that individual to be up at 3 a.m. connecting from China. AI can monitor those patterns of normalcy,” he says.