无人机系统安全靶场构建与攻防验证设计

李宇佳; 张辉; 多滨; 王梓斌; 周让; 李冬芬

doi:10.11959/j.issn.2096-109x.2026010

您当前的位置：

首页 >

文章列表页 >

无人机系统安全靶场构建与攻防验证设计

学术论文 | 更新时间：2026-05-26

- 无人机系统安全靶场构建与攻防验证设计
- Unmanned aerial vehicle system security cyber range construction and attack-defense validation design
- 网络与信息安全学报 2026年12卷第1期页码：54-73
- 作者机构：
  
  1.成都理工大学计算机与网络安全学院，四川成都 610059
  2.北京信息系统安全技术重点实验室北京100093
- 作者简介：
  
  李宇佳（2001- ），男，湖南衡阳人，成都理工大学计算机与网络安全学院硕士生，主要研究方向为无人机系统安全。
  张辉（1983- ），男，山东蓬莱人，成都理工大学计算机与网络安全学院讲师，主要研究方向为网络安全、密码学。
  多滨（1982− ），男，河北衡水人，成都理工大学计算机与网络安全学院教授，主要研究方向为无人集群系统安全、无人集群智能组网与协同通信关键技术。
  王梓斌（1982− ），男，山东莱阳人，北京信息系统安全技术重点实验室高级工程师，主要研究方向为无线网络安全、无人机系统安全。
  周让（1987− ），男，重庆人，成都理工大学研究员，主要研究方向为密码学、访问控制安全及数据安全。
  李冬芬（1979− ），女，青海海东人，成都理工大学教授，主要研究方向为信息安全、移动互联安全、量子密码通信等。
- 基金信息：
  
  国家自然科学基金(62172060);四川省高等学校创新性实验项目“智能无人系统安全创新实验”;2024－2026年成都理工大学高等教育人才培养质量和教学改革项目(JG2420017;JG2430165)
- DOI：10.11959/j.issn.2096-109x.2026010
  中图分类号： TP393
- 收稿：2025-08-13，
  
  修回：2025-12-13，
  
  纸质出版：2026-02-25
- 稿件说明：
移动端阅览
李宇佳, 张辉, 多滨, 等. 无人机系统安全靶场构建与攻防验证设计[J]. 网络与信息安全学报, 2026, 12(1): 54-73.

Li Yujia, Zhang Hui, Duo Bin, et al. Unmanned aerial vehicle system security cyber range construction and attack-defense validation design[J]. Chinese Journal of Network and Information Security, 2026, 12(1): 54-73.
李宇佳, 张辉, 多滨, 等. 无人机系统安全靶场构建与攻防验证设计[J]. 网络与信息安全学报, 2026, 12(1): 54-73. DOI： 10.11959/j.issn.2096-109x.2026010.

Li Yujia, Zhang Hui, Duo Bin, et al. Unmanned aerial vehicle system security cyber range construction and attack-defense validation design[J]. Chinese Journal of Network and Information Security, 2026, 12(1): 54-73. DOI： 10.11959/j.issn.2096-109x.2026010.

摘要

无人机技术当前被广泛应用于农业、物流、环境监测等领域，其安全问题逐渐成为研究的焦点。但当前无人机安全研究中的仿真测试平台存在无法系统有效地开展威胁分析并识别攻击类型与风险点、难以生成高质量攻击数据集以支撑入侵检测模型训练、无法实现攻防迭代验证等问题。针对上述问题，提出了一套无人机攻防闭环验证的实验框架，设计了一个包含基础设施层、模拟层、通信层、应用层和智能调度层5层架构的新型人工智能辅助无人机系统安全靶场。借助靶场提供的仿真测试环境，构建了从Wi-Fi发现、密码破解到指令欺骗的综合攻击场景。利用在该攻击场景下生成的实验数据，设计了一种基于单类支持向量机的入侵检测系统，经攻防迭代调整并不断优化实验参数，该入侵检测系统在指令欺骗攻击检测任务中的检测精确率由85.6%提升至93.8%，相比基于经典局部离群因子算法构建的模型，优化后的单类支持向量机模型检测精确率在多种攻击场景下均更具优势，证实了所提出的无人机系统安全靶场在威胁分析、数据集构建和攻防闭环验证方面的系统性、完备性和有效性。

Abstract

Unmanned aerial vehicle (UAV) technology is currently widely applied in fields such as agriculture

logistics and environmental monitoring

and its security issues have gradually become a research focus. However

in current UAV security research

existing simulation and testing platforms have problems: effective and systematic threat analysis cannot be carried out to identify attack types and risk points; high-quality attack datasets are difficult to be generated to support the training of intrusion detection models; “attack-defense iterative verification” cannot be realized

that is

the model is tested by attacks and then further optimized according to the results.To address the above problems

an experimental framework for UAV attack-defense closed-loop verification was proposed. A new artificial intelligence-assisted UAV system security testbed with a five-layer architecture (infrastructure layer

simulation layer

communication layer

application layer and intelligent scheduling layer) was designed and implemented. With the simulation test environment provided by the testbed

a comprehensive attack scenario covering Wi-Fi discovery

password cracking to command spoofing was constructed. Using the experimental data generated in this attack scenario

an intrusion detection system based on one-class support vector machine was designed. After iterative adjustment of attack and defense and continuous optimization of experimental parameters

the detection precision of the intrusion detection system for command spoofing attacks was improved from 85.6% to 93.8%. Compared with the model constructed based on the classic local outlier factor algorithm

the optimized one-class support vector machine model has more advantages in detection precision under various attack scenarios

which verifies that the proposed UAV system security testbed is systematic

complete and effective in threat analysis

dataset construction and attack-defense closed-loop verification.

关键词

Keywords

references

陈广承 , 柏艺琴 . 民航局《轻小无人机运行规定》解读 [J ] . 中国应急管理 , 2016 ( 1 ): 40 - 41 .

Chen G C , Bai Y Q . Interpretation of civil aviation administration’s regulations on the operation of light and small unmanned aerial vehicles [J ] . China Emergency Management , 2016 ( 1 ): 40 - 41 .

张军 , 陈磊 , 高智杰 , 等 . 低空无人机技术研究现状与展望 [J ] . 中国工程科学 , 2025 , 27 ( 2 ): 73 - 85 .

Zhang J , Chen L , Gao Z J , et al . Low-altitude unmanned aerial vehicle technology: current status and prospects [J ] . Strategic Study of Chinese Academy of Engineerng , 2025 , 27 ( 2 ): 73 - 85 .

Huang X . The small-drone revolution is coming: scientists need to ensure it will be safe [J ] . Nature , 2025 , 637 ( 8044 ): 29 - 30 .

Florido-Benítez L . The types of hackers and cyberattacks in the aviation industry [J ] . Journal of Transportation Security , 2024 , 17 ( 1 ): 13 .

Gomez-Thomas R . From corruption to combat: the militarization of organized crime in mexico [D ] . Waltham : Brandeis University , 2025 .

Pratama D , Moon J , Ari Laksmono A M , et al . Behind the wings: the case of reverse engineering and drone hijacking in DJI enhanced Wi-Fi protocol [C ] // Proceedings of the 2024 International Conference on Platform Technology and Service (PlatCon) . Piscataway : IEEE Press , 2025 : 127 - 132 .

蒋玉长 , 蒋利兵 , 黄凯 . FL-IoV: 基于联邦学习的综合车联网入侵检测方法 [J ] . 网络与信息安全学报 , 2025 , 11 ( 4 ): 127 - 140 .

Jiang Y C , Jiang L B , Huang K . FL-IoV: comprehensive intrusion detection method for Internet of vehicles based on federated learning [J ] . Chinese Journal of Network and Information Security , 2025 , 11 ( 4 ): 127 - 140 .

章阳 , 顾宏宇 , 冯博豪 , 等 . 语义通信下基于强化学习的无人机通信容错协同控制 [J ] . 网络与信息安全学报 , 2024 , 10 ( 2 ): 69 - 80 .

Zhang Y , Gu H Y , Feng B H , et al . Semantic communication aware reinforcement learning for communication fault-tolerant UAV collaborative control [J ] . Chinese Journal of Network and Information Security , 2024 , 10 ( 2 ): 69 - 80 .

Panda D K , Guo W S . Fragility impact of RL based advanced air mobility under gradient attacks and packet drop constraints [C ] // Proceedings of the 2023 IEEE 98th Vehicular Technology Conference (VTC2023-Fall) . Piscataway : IEEE Press , 2023 : 1 - 7 .

Duo B , Luo J S , Li Y L , et al . Joint trajectory and power optimization for securing UAV communications against active eavesdropping [J ] . China Communications , 2021 , 18 ( 1 ): 88 - 99 .

Huang K W , Wang H M . Combating the control signal spoofing attack in UAV systems [J ] . IEEE Transactions on Vehicular Technology , 2018 , 67 ( 8 ): 7769 - 7773 .

Rodday N M . Exploring security vulnerabilities of unmanned aerial vehicles [D ] . Enschede : University of Twente , 2015 .

Pandey G K , Gurjar D S , Nguyen H H , et al . Security threats and mitigation techniques in UAV communications: a comprehensive survey [J ] . IEEE Access , 2022 , 10 : 112858 - 112897 .

Omar T , Duran T , Al-Tarazi M , et al . SDR based replay attack for drone intervention [C ] // Proceedings of the 2024 Wireless Telecommunications Symposium (WTS) . Piscataway : IEEE Press , 2024 : 1 - 5 .

Lyu C Y , Zhan R J . Global analysis of active defense technologies for unmanned aerial vehicle [J ] . IEEE Aerospace and Electronic Systems Magazine , 2022 , 37 ( 1 ): 6 - 31 .

Wei X M , Ma J F , Sun C . A survey on security of unmanned aerial vehicle systems: attacks and countermeasures [J ] . IEEE Internet of Things Journal , 2024 , 11 ( 21 ): 34826 - 34847 .

Abdulrazak C . Cybersecurity threat analysis and attack simulations for unmanned aerial vehicle networks [J ] . arXiv: 2404.16842 , 2024 .

Kim Y , Cho K , Kim S . Challenges in dynamic analysis of drone firmware and its solutions [J ] . IEEE Access , 2024 , 12 : 106593 - 106604 .

Florido-Benítez L . Identifying and classifying cyberattacks on airports [J ] . Cyber Security: A Peer-Reviewed Journal , 2024 , 8 ( 1 ): 63 - 79 .

Cao Y L , Wang N F , Xiao C W , et al . Invisible for both camera and LiDAR: security of multi-sensor fusion based perception in autonomous driving under physical-world attacks [C ] // Proceedings of the 2021 IEEE Symposium on Security and Privacy (SP) . Piscataway : IEEE Press , 2021 : 176 - 194 .

Fu C H , Li S H , Yuan X N , et al . Ad2Attack: adaptive adversarial attack on real-time UAV tracking [C ] // Proceedings of the 2022 International Conference on Robotics and Automation (ICRA) . Piscataway : IEEE Press , 2022 : 5893 - 5899 .

陈世康 , 周冰 , 曹宝 , 等 . 无人机安全通信协议研究综述 [J ] . 通信技术 , 2024 , 57 ( 3 ): 213 - 221 .

Chen S K , Zhou B , Cao B , et al . Literature review of secure communication protocols for UAV [J ] . Communications Technology , 2024 , 57 ( 3 ): 213 - 221 .

黄明义 , 邹福泰 , 周纸墨 , 等 . 基于知识图谱和污点传播的网络攻击检测方法 [J ] . 网络与信息安全学报 , 2025 , 11 ( 1 ): 151 - 164 .

Huang M Y , Zou F T , Zhou Z M , et al . Network attack detection method based on knowledge graph and taint propagation [J ] . Chinese Journal of Network and Information Security , 2025 , 11 ( 1 ): 151 - 164 .

Whelan J , Sangarapillai T , Minawi O , et al . UAV attack dataset [J ] . IEEE Dataport , 2020 , 167 ( 1 ): 1561 - 1573 .

Whelan J , Sangarapillai T , Minawi O , et al . Novelty-based intrusion detection of sensor attacks on unmanned aerial vehicles [C ] // Proceedings of the 16th ACM Symposium on QoS and Security for Wireless and Mobile Networks . New York : ACM , 2020 : 23 - 28 .

佘丁辰 , 王威 , 王加琪 , 等 . 基于收缩自编码器的无人机GPS欺骗攻击协同检测方法 [J ] . 信号处理 , 2024 , 40 ( 4 ): 706 - 718 .

She D C , Wang W , Wang J Q , et al . Collaborative detection method of UAV GPS spoofing attack based on shrink autoencoder [J ] . Journal of Signal Processing , 2024 , 40 ( 4 ): 706 - 718 .

文霞 . 小型无人机抵抗GPS欺骗攻击的SVM-CNN模型研究 [J ] . 计算机技术与发展 , 2025 , 35 ( 8 ): 166 - 172 .

Wen X . Research on SVM-CNN models for small UAVs to resist GPS spoofing attacks [J ] . Computer Technology and Development , 2025 , 35 ( 8 ): 166 - 172 .

Wang S Q , Wang J , Su C H , et al . Intelligent detection algorithm against UAVs' GPS spoofing attack [C ] // Proceedings of the 2020 IEEE 26th International Conference on Parallel and Distributed Systems (ICPADS) . Piscataway : IEEE Press , 2021 : 382 - 389 .

王路阳 , 孙一宸 , 于明鑫 , 等 . 基于TimeGAN-LSTM的无人机GPS欺骗干扰检测模型 [J ] . 电子测量与仪器学报 , 2023 , 37 ( 6 ): 122 - 135 .

Wang L Y , Sun Y C , Yu M X , et al . UAV GPS spoofing detection model based on TimeGAN-LSTM [J ] . Journal of Electronic Measurement and Instrumentation , 2023 , 37 ( 6 ): 122 - 135 .

Samriya J K , Kumar M , Tiwari R . Energy-aware ACO-DNN optimization model for intrusion detection of unmanned aerial vehicle (UAVs) [J ] . Journal of Ambient Intelligence and Humanized Computing , 2023 , 14 ( 8 ): 10947 - 10962 .

Wu Y X , Yang L , Zhang L , et al . Intrusion detection for unmanned aerial vehicles security: a tiny machine learning model [J ] . IEEE Internet of Things Journal , 2024 , 11 ( 12 ): 20970 - 20982 .

Hassler S , Mughal U , Ismail M . Cyber-physical dataset for UAVs under normal operations and cyber-attacks [J ] . IEEE Dataport , 2023 , 10 .

赵长啸 , 方玉麟 , 汪克念 . 基于BiTCN的无人机指挥控制链路DoS攻击检测方法 [J ] . 航空学报 , 2025 , 47 ( 1 ): 332048 .

Zhao C X , Fang Y L , Wang K N . BiTCN-based DoS attack detection method for UAV command and control link [J ] . Acta Aeronautica et Astronautica Sinica , 2025 , 47 ( 1 ): 332048 .

Hadi H J , Cao Y , Khan M K , et al . UAV-NIDD: a dynamic dataset for cybersecurity and intrusion detection in UAV networks [J ] . IEEE Transactions on Network Science and Engineering , 2025 , 12 ( 4 ): 2739 - 2757 .

Madaan R , Gyde N , Vemprala S , et al . AirSim drone racing lab [C ] // Proceedings of the Neurips 2019 competition and demonstration track . PMLR , 2020 : 177 - 191 .

Quan Q , Dai X H , Wang S . Multicopter design and control practice: a series experiments based on MATLAB and Pixhawk [M ] . Singapore : Springer Singapore , 2020 : 18 - 19 .

Schmittle M , Lukina A , Vacek L , et al . OpenUAV: a UAV testbed for the CPS and robotics community [C ] // Proceedings of the 2018 ACM/IEEE 9th International Conference on Cyber-Physical Systems (ICCPS) . Piscataway : IEEE Press , 2018 : 130 - 139 .

Zhou Z H , Dai Z P , Huang L Y , et al . UavNetSim-v1: a Python-based simulation platform for UAV communication networks [C ] // Proceedings of the 2025 IEEE/CIC International Conference on Communications in China (ICCC) . Piscataway : IEEE Press , 2025 : 1 - 6 .

Baidya S , Shaikh Z , Levorato M . FlyNetSim: an open source synchronized UAV network simulator based on NS-3 and ardupilot [C ] // Proceedings of the 21st ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems . New York : ACM , 2018 : 37 - 45 .

Dai X H , Ke C X , Quan Q , et al . RFlySim: Automatic test platform for UAV autopilot systems with FPGA-based hardware-in-the-loop simulations [J ] . Aerospace Science and Technology , 2021 , 114 : 106727 .

Xiao K , Tan S C , Wang G H , et al . XTDrone: a customizable multi-rotor UAVs simulation platform [C ] // Proceedings of the 2020 4th International Conference on Robotics and Automation Sciences (ICRAS) . Piscataway : IEEE Press , 2020 : 55 - 61 .

Devine T R , Cunningham D J , Hasselman T J K , et al . INDRA: a drone penetration testing platform for cybersecurity education [C ] // Foundations of Computer Science and Frontiers in Education: Computer Science and Computer Engineering . Cham : Springer , 2025 : 235 - 251 .

高健 . 虚实结合的无人机靶场设计与实现 [D ] . 西安：西安电子科技大学 , 2022 .

Gao J . Design and implementation of UAV cyberRange co-mbining virtual and real [D ] . Xi’an : Xidian University , 2022 .

邹星 , 胡宁 , 顾钊铨 , 等 . 网络靶场研究现状与展望 [J ] . 网络与信息安全学报 , 2024 , 10 ( 5 ): 1 - 22 .

Zou X , Hu N , Gu Z Q , et al . Cyber ranges: survey and perspective [J ] . Chinese Journal of Network and Information Security , 2024 , 10 ( 5 ): 1 - 22 .

王佰玲 , 刘红日 , 张耀方 , 等 . 工业控制系统安全仿真关键技术研究综述 [J ] . 系统仿真学报 , 2021 , 33 ( 6 ): 1466 - 1488 .

Wang B L , Liu H R , Zhang Y F , et al . Review on key technologies of industrial control system security simulation [J ] . Journal of System Simulation , 2021 , 33 ( 6 ): 1466 - 1488 .

Davis J , Magrath S . A survey of cyber ranges and testbeds [J ] . 2013 : 1 - 38 .

Ukwandu E , Ben-Farah M A , Hindy H , et al . A review of cyber-ranges and test-beds: current and future trends [J ] . Sensors , 2020 , 20 ( 24 ): 7148 .

Nikolaiev M , Novotarskyi M . Comparative review of drone simulators [J ] . Information, Computing and Intelligent Systems , 2024 ( 4 ): 79 - 98 .

白天翔 , 王帅 , 沈震 , 等 . 平行机器人与平行无人系统: 框架、结构、过程、平台及其应用 [J ] . 自动化学报 , 2017 , 43 ( 2 ): 161 - 175 .

Bai T X , Wang S , Shen Z , et al . Parallel robotics and parallel unmanned systems: framework, structure, process, platform and applications [J ] . Acta Automatica Sinica , 2017 , 43 ( 2 ): 161 - 175 .

Bagchi P , Maheshwari R , Bera B , et al . Public blockchain-envisioned security scheme using post quantum lattice-based aggregate signature for Internet of drones applications [J ] . IEEE Transactions on Vehicular Technology , 2023 , 72 ( 8 ): 10393 - 10408 .

Son S , Kwon D , Lee S , et al . Design of secure and lightweight authentication scheme for UAV-enabled intelligent transportation systems using blockchain and PUF [J ] . IEEE Access , 2023 , 11 : 60240 - 60253 .

Jalil-Hadi H , Cao Y , Li S F , et al . Real-time collaborative intrusion detection system in UAV networks using deep learning [J ] . IEEE Internet of Things Journal , 2024 , 11 ( 20 ): 33371 - 33391 .

武阳 , 刘靖 . 面向图像分析领域的黑盒对抗攻击技术综述 [J ] . 计算机学报 , 2024 , 47 ( 5 ): 1138 - 1178 .

Wu Y , Liu J . A survey on black-box adversarial attack in image analysis [J ] . Chinese Journal of Computers , 2024 , 47 ( 5 ): 1138 - 1178 .

王群 , 李馥娟 , 倪雪莉 , 等 . 域间路由安全增强及区块链技术的应用研究 [J ] . 计算机科学与探索 , 2024 , 18 ( 12 ): 3144 - 3174 .

Wang Q , Li F J , Ni X L , et al . Research on blockchain-based inter-domain routing security enhancement [J ] . Journal of Frontiers of Computer Science Technology , 2024 , 18 ( 12 ): 3144 - 3174 .

邢颖 . 基于可解释性人工智能的软件工程技术方法综述 [J ] . 计算机科学 , 2023 , 50 ( 5 ): 3 - 11 .

Xing Y . Review of software engineering techniques and methods based on explainable artificial intelligence [J ] . Computer Science , 2023 , 50 ( 5 ): 3 - 11 .

浏览量

189

下载量

CSCD

文章被引用时，请邮件提醒。

提交

工具集

关联资源

移动边缘计算安全防御研究

移动通信网鉴权认证综述

移动云计算中一种新的跨层信誉机制

面向行为的内网空间安全态势建模与分析

云计算中图像数据处理的隐私保护