Alam and Sehatbakhsh are Ph.D. students in the Georgia Tech School of Computer Science (CS), and Callan is a postdoctoral fellow in Tech’s School of Electrical and Computer Engineering (ECE). They are co-advised by Alenka Zajic, an assistant professor in ECE, and Milos Prvulovic, a professor in CS.

The Internet of Things (IoT) has introduced new security risks for both consumers and businesses. Mitigation of these risks is difficult in part because IoT devices often have limited resources that can be leveraged to monitor their security, and often have limited hardware and system support for isolation and protection. Unfortunately, existing malware detection techniques require significant computation power and resources on the monitored device itself, making their deployment on IoT devices challenging.

To mitigate this problem, this CS/ECE research team has developed a new method to detect malware by externally observing Electromagnetic (EM) signals emitted by an IoT system and showed a demo of how it works at the IEEE HOST Symposium. The system collects EM signals from a distance of a few meters, records them, and uses a spectral monitoring algorithm that the team developed to detect any malware intrusion on an IoT system.