论文标题
一种基于代理的自我保护方法，可确保无人机网络中无人机之间的通信
An agent-based self-protective method to secure communication between UAVs in unmanned aerial vehicle networks
论文作者
论文摘要
由于其特征性特征，例如高度动态的网络拓扑，露天无线环境和高移动性，因此无人机（无人驾驶飞机网络）可能变得容易受到威胁和攻击的影响。由于以前的工作集中在基于经典和元启发式的方法上，因此这些方法都没有一种自适应方法。在本文中，以表格的形式研究了先前方法的挑战和弱点。此外，我们建议基于人类免疫系统（HIS）的基于代理的自我保护方法（ASP-UAVN）。在ASP-UAS中，根据自我保护系统选择了从源无人机到目标无人机的最安全路线。在这种方法中，使用使用人工免疫系统（AIS）的多机构系统来检测攻击无人机并选择最安全的路线。在建议的ASP-UAVN中，路由请求数据包（RREQ）最初是从源无人机传输到目标无人机以检测现有路由的。然后，一旦收到了路由回复数据包（RREP），就采用了一种使用代理的自我保护方法，并采用知识库选择最安全的路线并检测攻击无人机。提出的ASP-UAVN通过两种方式进行了验证和评估：仿真和理论分析。 The results of simulation evaluation and theory analysis showed that the ASP-UAS increases the Packet Delivery Rate (PDR) by more than 17.4, 20.8, and 25.91%, and detection rate by more than 17.2, 23.1, and 29.3%, and decreases the Packet Loss Rate (PLR) by more than 14.4, 16.8, and 20.21%, the false-positive and false-negative rate by more than 16.5, 25.3和31.21％的Suas-His，SFA和Bruids方法的25.3％。
UAVNs (unmanned aerial vehicle networks) may become vulnerable to threats and attacks due to their characteristic features such as highly dynamic network topology, open-air wireless environments, and high mobility. Since previous work has focused on classical and metaheuristic-based approaches, none of these approaches have a self-adaptive approach. In this paper, the challenges and weaknesses of previous methods are examined in the form of a table. Furthermore, we propose an agent-based self-protective method (ASP-UAVN) for UAVNs that is based on the Human Immune System (HIS). In ASP-UAS, the safest route from the source UAV to the destination UAV is chosen according to a self-protective system. In this method, a multi-agent system using an Artificial Immune System (AIS) is employed to detect the attacking UAV and choose the safest route. In the proposed ASP-UAVN, the route request packet (RREQ) is initially transmitted from the source UAV to the destination UAV to detect the existing routes. Then, once the route reply packet (RREP) is received, a self-protective method using agents and the knowledge base is employed to choose the safest route and detect the attacking UAVs. The proposed ASP-UAVN has been validated and evaluated in two ways: simulation and theoretical analysis. The results of simulation evaluation and theory analysis showed that the ASP-UAS increases the Packet Delivery Rate (PDR) by more than 17.4, 20.8, and 25.91%, and detection rate by more than 17.2, 23.1, and 29.3%, and decreases the Packet Loss Rate (PLR) by more than 14.4, 16.8, and 20.21%, the false-positive and false-negative rate by more than 16.5, 25.3, and 31.21% those of SUAS-HIS, SFA and BRUIDS methods, respectively.
