Machine learning and blockchain technologies for cybersecurity in connected vehicles

Future connected and autonomous vehicles (CAVs) must be secured againstcyberattacks for their everyday functions on the road so that safety of passengersand vehicles can be ensured. This article presents a holistic review of cybersecurityattacks on sensors and threats regardingmulti-modal sensor fusion. A compre-hensive review of cyberattacks on intra-vehicle and inter-vehicle communicationsis presented afterward. Besides the analysis of conventional cybersecurity threatsand countermeasures for CAV systems,a detailed review of modern machinelearning, federated learning, and blockchain approach is also conducted to safe-guard CAVs. Machine learning and data mining-aided intrusion detection systemsand other countermeasures dealing with these challenges are elaborated at theend of the related section. In the last section, research challenges and future direc-tions are identified

Crosstalk in modern software defined radio for the implementation of frequency modulated continuous wave radar

Abstract This study investigates crosstalk and leakage in the Software Defined Radio implementation of Frequency Modulated Continuous Wave (FMCW) radar systems. Empirical measurements of leakage power were conducted during the implementation of FMCW radar using National Instruments Universal Software Radio Peripheral (USRP) boards. Mono‐static and bi‐static/distributed Transmitter‐Receiver configurations are compared for low power micro‐Doppler applications. The impact of crosstalk on the dynamic range of the target is also investigated. The impact of electric noise generated by a windy source on the receiving USRP is also investigated. Furthermore, a simple splitter based approach is proposed to overcome the challenge of synchronisation or recovery of transmitted waveform in distributed configurations