Radar systems have long been essential for safe navigation in various transportation sectors, including aviation, maritime, and automotive. While these systems provide invaluable situational awareness and decision-making capabilities, they increasingly become targets for malicious actors aiming to disrupt their normal operations. Electronic countermeasures (ECM) have traditionally been the predominant form of attack. However, recent findings have uncovered their vulnerability to cyber-based actions, capitalizing on their digitization and network connectivity. In this paper, we propose a novel threat model that exploits cyber attack capabilities against radar systems to simulate the effects of ECM. This model goes beyond known attacks by introducing a deceptive element, challenging attribution. To evaluate the feasibility of these attacks, extensive experimentation is conducted using a realistic case study involving the maritime domain. Through this research, we aim to highlight the evolving threats facing radar systems and the need for comprehensive security measures.

This paper uses data processing techniques to reduce the required transmission bandwidth in ship-to-shore communications. The proposed framework (ONline Efficient Sources Transmission Optimizer - ONESTO) leverages state-of-the-art technologies and novel algorithms to automatically optimize transmissions under structural (e.g., available bandwidth, fixed packet overhead) and user-defined (e.g., maximum latency) constraints. In addition, ONESTO authenticates and encrypts the communication between the ship and the shore via mainstream free and open-source software components. Initially, we present the abstract mathematical formulation of the problem, with its assumptions, goal function, constraints, and significant quantities. Then, we introduce the architecture of a system capable of continuously estimating the compressibility, processing and transmission time of streaming data. Such estimations allow ONESTO to calculate and apply optimal parameters for achieving the best compression ratio. Lastly, using a prototypical implementation, we evaluate the system performance with a Class B ship simulator on two realistic use cases. Our experiments show an excellent compression ratio with maritime protocols (more than 40:1) and a limited latency impact, demonstrating the approach’s viability.