The civilian Automatic Identification System (AIS) has no inherent protection against spoofing. Spoofed AIS messages have the potential to interfere with the safe navigation of a vessel by, amongst other approaches, spoofing maritime virtual aids to navigation and/or differential global navigation satellite system (DGNSS) correction data conveyed across it. Acting maliciously, a single transmitter may spoof thousands of AIS messages per minute with the potential to cause considerable nuisance; compromising information provided by AIS intended to enhance the mariner's situational awareness. This work describes an approach to authenticate AIS messages using public key cryptography (PKC) and thus provide unequivocal evidence that AIS messages originate from genuine sources and so can be trusted. Improvements to the proposed AIS authentication scheme are identified which address a security weakness and help avoid false positives to spoofing caused by changes to message syntax. A channel loading investigation concludes that sufficient bandwidth is available to routinely authenticate all AIS messages whilst retaining backwards compatibility by carrying PKC ‘digital signatures’ in a separate VHF Data Exchange System (VDES) side channel.

A spoofing attack on a global navigation satellite system (GNSS) receiver is a threat to a significant community of GNSS users due to the high stakes involved. This paper investigates the use of slope based metrics for the detection of spoofing. The formulation of slope based metrics involves monitoring correlators along with tracking correlators in the receiver's channel, which are slaved to the prompt tracking correlator. In this study, using some candidate metrics, detectors have been formed through the analysis of simulated spoofing attacks. A theoretical variance of each metric has also been calculated as a reference for the threshold. A threshold is estimated using the measured variance from the clean signals, for specific false alarm rate. By using the measured threshold, detectors are formed based on slope metrics. These detectors have been tested using TEXBAT data. The results show that the differential slope metrics have good performance. The results have also been compared with some other techniques of spoofing detection.