For scammers phishing for personal information, financial data and intellectual property, higher education is already a prime target. Armed with artificial intelligence, those cyber criminals become even better poised to launch AI cyberattacks against colleges and universities.
The Global Information Security Workforce Study predicts that the cybersecurity workforce gap will reach 1.8 million by 2022, a 20-percent jump from 2015. The same study found that 68 percent of North American workers blame this gap on a lack of qualified personnel. It doesn’t help that colleges and universities often struggle to match the allure of more lucrative private-sector salaries, thus narrowing the pipeline of skilled cybersecurity professionals even further.
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With constrained budgets and too few workers, higher education faces an even harder time protecting its data. Fortunately, cyber criminals aren’t the only ones who can capitalize on artificial intelligence: the good guys can use the same AI technology to shore up skills gaps.
Artificial Intelligence Technology Combs Through Big Data
Humans cannot keep up with the volume of potential attacks and intrusions the way that AI can, says Neal Fisch, director of enterprise services and security at California State University Channel Islands.
“There is much that AI can do to bolster and enhance a cybersecurity program, including making up for staff shortages,” he says. It can be particularly useful in research and analysis of large datasets because AI can sift through and address issues much faster and more efficiently than a person can.
Meanwhile, relieving individuals of such tasks allows them to do the work that humans are actually better suited for. “AI is just another tool in a cybersecurity professional’s belt that can help them focus on the more critical and strategic work to be done in cybersecurity by relieving them of the more repetitive tasks,” Fisch adds.
“It’s a needle in a haystack sort of thing,” says Von Welch, executive director for cybersecurity innovations at Indiana University and director of IU’s Center for Applied Cybersecurity Research. “The problem is not finding the incident. It’s getting rid of the hay that’s surrounding the needle that’s the incident.”
AI Technology Can Analyze Reports
Mike Spisak, CTO of security for IBM Garage, says that AI can help sort through the massive amounts of information released on a monthly basis. “It’s impossible for anyone to possibly ingest that much data,” he says, “but this is something computers can do very well,” especially because AI’s natural language understanding has improved enough to comprehend context (for instance, the difference between a healthcare virus versus a computing virus. This is a specialty of IBM’s Watson, which has already been used to create a teaching assistant named Jill Watson at Georgia’s Institute of Technology.
“AI can create insights or reasoning, which will allow a lesser skilled analyst to have a trusted advisor to help them correlate relationships and threats that are happening in the environment in real time,” Spisak says.
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In 10 years, Fisch says, “most of the day-to-day work done by cybersecurity professionals will be done using some form of AI. The size and number of datasets requiring review and action will grow exponentially. As AI continues to mature,” he continues, “so will the cybersecurity profession’s use for it, such as having AI work on more strategic and cybersecurity issues.”
AI Technology Makes Entry-Level Jobs More Interesting
AI can also help improve retention rates by making entry-level cybersecurity jobs “less dull,” says Kayne McGladrey, CISO and CIO of Pensar and a member of the IEEE. “We get people out of school, and they are excited to be on the team. Then, on their first day, they’re handed a checklist: here’s the things you will do and the order in which you will do them.”
A job that consists of reading logs and chasing down false leads may not be enticing enough to keep workers around, especially when those kinds of skills are in demand at higher pay elsewhere. “We’re asking people to act like machines,” he says, “and that’s not very a very effective engagement model.”
Instead, AI and machine learning can review the data and extract threads. Next, entry-level professionals “can focus on what humans are good at, which is using some level of intuition to say, ‘Let’s look at this one a little more,’” McGladrey says.
While Welch believes that AI is still in its hype phase, he sees its potential in helping organizations “get to the point where we’re applying the human brain to what we’re more confident are human problems.”
