Secured Localization on the Drone Networks for Search and Rescue operations

The proliferation of location-aware applications for the Internet of drones (IoD) introduces security attacks such as false positioning, jamming and malicious data. Localization in IoD can be compromised by injecting false locations, and data from malicious nodes and making the battery of drones drain quickly by jamming attacks (repeated retransmission/disruptive data transmission). Therefore, to overcome these issues, this research proposes a secured and trustworthy localization algorithm based on nature-inspired artificial intelligence. Additionally, data exchanged between ground sensor nodes and low-altitude drone sensor nodes are signed and the efficiency of the authentic location is validated for assurance of their authenticity. This process of merging security methodologies into the localization mechanisms enables mitigation of localization errors and improves the detection accuracy in the existence of malicious nodes, for unpredictable scenarios such as post-disaster search and rescue (SAR). The experimental results are evaluated in terms of parameters such as latency, throughput and percentage of the localization error.