# A Hierarchical Blockchain-Based Trust Measurement Method for Drone Cluster Nodes
## 1 Introduction  
In recent years, drone clusters have found increasingly widespread applications in both military and civilian fields, such as collaborative reconnaissance, real-time monitoring, and aerial base stations [1]. Unmanned aerial vehicle mobile ad hoc networks (UAV MANETs) represent a common communication network for drone clusters, which operate independently of ground-based communication infrastructure and establish distributed networks among the UAVs [2]. The trust degree of UAV nodes is an important influence point for drone cluster mission coordination, independent decision-making, and independent judgment [3]. The trust value of UAV nodes can not only help to select suitable UAVs to participate in tasks but also support resource allocation and task scheduling. However, when the drone cluster is far away from the management platform, facing a variety of network attacks and information interference, the UAV nodes may face cross-cluster reorganization, high dynamic entry and exit of trust clusters, etc. [4]. The trustworthiness inheritance of dynamically entering and exiting nodes and the trust re-evaluation of dynamic clusters become crucial. The rapid changes in the topology of UAV MANETs result in the instability of communication delay and link status [5; 6]. UAV nodes cannot continuously monitor neighbor nodes, but the comprehensive trust degree of UAV nodes can be calculated through the combination of node direct trust evaluation and recommended trust evaluation. Blockchain technology possesses characteristics of decentralization, immutability, and traceability, enabling secure data sharing. In the context of trust management mechanisms, blockchain can be employed to record the trustworthiness information of UAV nodes within the network. However, as the number of UAVs in the network increases, the blockchain also grows, leading to increased communication latency and operational burdens on the network [7]. In order to reduce the propagation delay of blocks and the communication overhead in UAV MANETs, a hierarchical blockchain approach is adopted for trustworthy historical data flow and inheritance [8]. This allows for cross-domain data sharing among UAVs, enhances the credibility of data transmission, improves the accuracy of UAV node trust measurement, supports autonomous mission coordination and collaborative decision-making capabilities, and ensures reliable task completion. 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. Another study [10] proposed a secure clustering scheme based on fuzzy classification trust, utilizing multi-criteria for classification and optimization to assess node trust. However, this scheme incurs higher energy consumption. Additionally, it assumes a cluster-level hierarchical structure for the network, which results in a higher probability of network failure. Alternatively, the literature [11] introduces a random repeat trust computation scheme that takes into account remaining energy and channel quality. This scheme directly specifies the weight for trust evaluation factors and computes node trust using a weighted average. Further, the literature [12] adopts a fuzzy C-Means clustering approach to categorize nodes into three groups. Simultaneously, it adjusts the evaluation factor weights and calculates trust degrees based on the clustering centers, thereby rewarding or penalizing nodes within the cluster. Addressing security concerns, the literature [13] employs fuzzy variables to characterize attributes associated with black holes, flooding, and packet discarding attacks prevalent in ad hoc networks. A fuzzy Petri network divides node trust levels into five tiers, facilitating fuzzy security verification among nodes.