A woman touches a hot stove, but thanks to the nervous system, she snatches her hand away before she gets too hurt. A virus enters the body, but the immune system fends off the invader before it can cause too much damage. What if our computers and smartphones could respond to security threats in the same proactive way our bodies respond to health threats?
A team of ECE researchers are developing a form of cybersecurity inspired by these human biological systems that detect and address threats in their earliest stages. The team will also offer training and research opportunities to students from underrepresented backgrounds.
The Partnership for Proactive Cybersecurity Training project is funded by a three-year, $3 million grant from the National Nuclear Security Administration's Minority Serving Institution Partnership Program. The UA, which was designated as a Hispanic-Serving Institution in 2018, is collaborating with Howard University, Navajo Technical University and Argonne National Laboratory.
"I felt we could learn about how the body protects us by reacting to threats and maybe apply it to cyber by building a 'cyber immune system,'" said Salim Hariri, professor and the project's principal investigator. "We're trying to build these abilities where, when somebody attacks your computer, these measures can detect the attack and act on it before you're even aware something is compromised."
The term "cybersecurity" might bring to mind images of government secrets and companies managing large quantities of information, but it's an important issue for anyone who owns a computer or smartphone.
"You carry around this phone that's networked to all kinds of servers, and your information is very vulnerable," said Tamal Bose, department head and co-investigator on the project. "Cyberspace is the domain where most wars are going to be fought in the future."
Machine learning is especially useful in a cybersecurity context because attackers, with a whole playbook of tactics at their disposal, often evolve their methods. How they attack a computer today might be different from the way they do it tomorrow, so the cybersecurity system must be able to learn as it goes along, detect changes in the environment and even anticipate changes before they occur.
Co-investigator and assistant professor Gregory Ditzler continues the analogy of a hand on a hot stove. "Once you put your hand down on that stove, you know not to touch it again, because it's hot," he said. "But how can you be prepared to recognize other dangers, like putting your hand in a toaster? This is where machine learning comes in."
The grant takes a two-pronged approach to improving the science of cybersecurity. While researchers develop these new techniques, they'll also be training students – especially underrepresented minority groups and women – to become highly skilled members of the cybersecurity workforce.
"The hottest jobs, and some of the highest-paid jobs, today are in cybersecurity," Hariri said. "If I were a student who wanted job security, a high salary and the chance to make a big impact on our society, this is the field I would want to study."
For more about the project in Spanish, please watch this story on Univision.
Para obtener más información, este proyecto en español, se puede ver en el canal de Univisión.