Abstract
The battlefield has evolved into a mobile and dynamic scenario where soldiers and heterogeneous military equipment exchange information in real-time and wirelessly. This fact brings to reality the Internet of Battlefield Things (IoBT). Wireless communications are key enablers for the IoBT, and their management is critical due to the spectrum scarcity and the increasing number of IoBT devices. In this sense, IoBT spectrum sensors are deployed on the battlefield to monitor the frequency spectrum, transmit over unoccupied bands, intercept enemy transmissions, or decode valuable information. However, IoBT spectrum sensors are vulnerable to heterogeneous cyber-attacks, and their accurate detection is an open challenge in the literature. Thus, this paper presents SpecForce, a security framework for IoBT spectrum sensors based on device behavioral fingerprinting and ML/DL techniques. SpecForce considers heterogeneous data sources to detect the most dangerous and recent cyber-attacks affecting IoBT spectrum sensors, such as impersonation, malware, and spectrum sensing data falsification attacks. To evaluate the SpecForce detection performance, it has been deployed on 25 real spectrum sensors, and results show almost perfect detection for the three cyber-attack families previously mentioned.
Sánchez, Pedro Miguel Sánchez