Towards Trust Model in Unmanned Aerial Vehicle Ad Hoc Networks

Abstract

Unmanned Aerial Vehicle ad hoc networks (UAANETs) are originally designed to work in a cooperative environment. These networks are vulnerable to a wide range of attacks due to the lack of predefined infrastructure and the dynamic topology. Security in ad hoc networks, in general, is handled through authentication and encryption. This can be considered as a heavy way to protect the network due to the lack of resources in the nodes. However, trust can be introduced to address a light weight solution for some security issues. In this paper, we focus on the concept of decentralized trust to design an efficient and trustful routing protocol, and ensure stable routes between nodes in spite of the rapidly changing topology, and to provide a mechanism for detecting malicious incorrect packet forwarding attacks. The proposed light-weight trust-quality routing protocol (TQAODV) provides two main functionalities: monitoring the behavior of the neighboring nodes and computing the trust value based on the historical information in the network. Moreover, the new proposed model reduces routing overhead and route discovery frequency. The simulations we used in NS-2 show that the proposed routing scheme gives better performance against attacks compared to the traditional Ad-hoc On-demand Distance Vector (AODV), and improves the packets delivery ratio with about 15%, routing packets overhead and average delay with about 20%, compared to trust AODV.

A Survey on Reputation Systems for UAV Networks

“…Trust [1,[4][5][6]13,17,18,20,25,29,35,36,40,46,49,[54][55][56][57][58][59][60][61][62][63][64][65][66][67].…”

“…A novel malicious node detection method, enhanced reputation calculation, involvement of a distributed trust concept in calculations, and overall performance improvements were proposed as a result of the challenges in unmanned aerial vehicle ad hoc network (UAANET) research, which include the lack of security and trustworthiness, resource overusage, energy consumption, memory constraints, and preventing selfish node attacks [57]. These challenges were addressed to achieve a fully trusted network in UAANET.…”

“…These challenges were addressed to achieve a fully trusted network in UAANET. A trustbased distributed technique was introduced for UAANET using the hidden Markov model (HMM) to address security and trust issues, including preventing selfish node attacks [57].…”

A Hierarchical Blockchain-Based Trust Measurement Method for Drone Cluster Nodes

“…Within the realm of UAV trust measurement research, the literature [9] employs data packet forwarding history and recommendation information from neighboring nodes to calculate the trustworthiness of other nodes. However, this trust mechanism exhibits a limitation in that it relies on a single trust assessment factor and cannot effectively address issues such as link failures.…”

“…The above research has laid a good foundation for the research on the trust evaluation model of UAV nodes, but some of the literature ignores the influence of trust timeliness on trust evaluation in the direct trust degree calculation [12,13], which can not reflect well on node behavior, which reduces the accuracy of trust calculation. The trust evaluation of UAVs in the other literature still has shortcomings such as the single trust evaluation factor [9,15], relatively fixed trust evaluation weight [11], high communication overhead [10,14,15], unreasonable trust evaluation [16], etc. Furthermore, while much of the current research is centered around assessing the reputation of UAVs, there is a notable lack of attention directed toward establishing robust mechanisms for credible reputation management.…”