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.

UAVN（无人飞行器网络）由于其特征，例如高度动态的网络拓扑，露天无线环境和高移动性，可能容易受到威胁和攻击。由于以前的工作集中在基于经典和基于元启发式的方法上，因此这些方法都没有自适应方法。在本文中，以表格的形式检查了先前方法的挑战和弱点。此外，我们为基于人类免疫系统（HIS）的UAVN提出了一种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从源无人机到目标无人机的最安全路线。在这种方法中，采用了使用人工免疫系统（AIS）的多主体系统来检测攻击的无人机并选择最安全的路线。在提出的ASP-UAVN中，首先将路由请求包（RREQ）从源UAV发送到目标UAV，以检测现有路由。然后，一旦接收到路由应答数据包（RREP），就使用代理和知识库的自我保护方法来选择最安全的路由并检测攻击的无人机。所提出的ASP-UAVN已通过两种方式进行了验证和评估：仿真和理论分析。仿真评估和理论分析的结果表明，ASP-UAS将数据包传输率（PDR）提高了17.4％，20.8％和25.91％以上，将检测率提高了17.2％，23.1％和29.3％以上，并降低了封包丢失率（PLR）超过SUAS-HIS的14.4、16.8和20.21％，误报率和误报率超过16.5、25.3和31.21％，