English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Ensuring the desired level of security is an important issue in all communicating systems, and it becomes more challenging in wireless environments. Flying Ad Hoc Networks (FANETs) are an emerging type of mobile network that is built using energy-restricted devices. Hence, the communications interface used and that computation complexity are additional factors to consider when designing secure protocols for these networks. In the literature, various solutions have been proposed to ensure secure and reliable internode communications, and these FANET nodes are known as Unmanned Aerial Vehicles (UAVs). In general, these UAVs are often detected as malicious due to an unintentional misbehavior related to the physical features of the UAVs, the communication mediums, or the network interface. In this paper, we propose a new context-aware trust-based solution to distinguish between intentional and unintentional UAV misbehavior. The main goal is to minimize the generated error ratio while meeting the desired security levels. Our proposal simultaneously establishes the inter-UAV trust and estimates the current context in terms of UAV energy, mobility pattern, and enqueued packets, in order to ensure full context awareness in the overall honesty evaluation. In addition, based on computed trust and context metrics, we also propose a new inter-UAV packet delivery strategy. Simulations conducted using NS2.35 evidence the efficiency of our proposal, called , at ensuring high detection ratios > 87% and high accuracy with reduced end-to-end delay, clearly outperforming previous proposals known as , - , and .

UNION: A Trust Model Distinguishing Intentional and Unintentional Misbehavior in Inter-UAV Communication