簡易檢索 / 詳目顯示

回結果列表
研究生： 余祐安
Yu, You-An
論文名稱： 低軌衛星非地面網路星內波束交換之使用者設備端欺騙訊號偵測
User Equipment-Side Spoofing Detection for LEO NTN Intra-Satellite Beam Handover
指導教授： 莊智清
Juang, Jyh-Ching
學位類別： 碩士
Master
系所名稱： 電機資訊學院 - 電機工程學系
Department of Electrical Engineering
論文出版年： 2026
畢業學年度： 114
語文別： 英文
論文頁數： 65
中文關鍵詞： 實體層安全 、物理層認證 、頻率殘差 、最大相關熵準則 、序列檢測
外文關鍵詞： Physical Layer Security, Physical Layer Authentication, Frequency Residuals, Maximum Correntropy Criterion, Sequential Detection
相關次數： 點閱：75  下載：0 
分享至:
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報

    • 在通訊安全中，系統除須保障機密性、完整性與可用性外，亦須確認訊息物理來源之真實性。於低軌衛星非地面網路星內波束交換中，協定層雖可維持連線，卻難以保證接收訊號仍與合法衛星幾何一致；現有實體層欺騙偵測亦較少處理跨交換連續監測、參考污染，以及接近雜訊底限之弱殘差偏差等問題。
    本文建立觀測層級威脅模型，將使用者設備端頻率殘差表述為二元假設檢定，並提出結合最大相關熵準則卡爾曼濾波器觀測穩定化、受保護參考基準、序列證據累積與有限狀態機閘控之序列式防禦架構，使監測流程得以跨越交換暫態持續運作。
    波形層級第五代新無線電非地面網路模擬結果顯示：在不同衛星—使用者幾何條件下，偵測性能隨攻擊引入之頻率偏差相對量測雜訊之強度而變化；於既定校準操作點下，主要仰角工作區間誤警受控，且該偏差對雜訊強度愈大時事件偵測率愈高；消融實驗驗證各模組之結構性貢獻；偵測延遲與恢復對幾何失配穩健，主要受低訊雜比影響。
    協定層安全驗證邏輯身分，卻無法直接檢查物理波形來源。使用者設備端頻率一致性驗證可於波束交換中持續監測殘差偏移，不取代協定層機制，但可補強物理來源一致性，作為低軌衛星非地面網路之實體層輔助防線。

    In communication security, systems must protect confidentiality, integrity, and availability, and must also verify the physical origin of received signals. In low Earth orbit (LEO) non-terrestrial network (NTN) intra-satellite beam handover, protocol-layer procedures maintain connectivity but cannot guarantee that received signals remain consistent with legitimate satellite geometry. Existing physical-layer spoofing detection also seldom addresses cross-handover continuous monitoring, reference contamination, and weak residual bias near the noise floor.
    This thesis develops an observation-level threat model, formulates frequency residuals at the user equipment (UE) side as a binary hypothesis test, and proposes a sequential defense framework that combines maximum correntropy criterion Kalman filter (MCCKF) observation stabilization, protected reference maintenance, sequential evidence accumulation, and finite state machine (FSM) gating so that monitoring can continue across handover transients.
    Waveform-level 5G New Radio (NR) NTN simulation results show that detection performance follows the strength of attack-induced frequency bias relative to the measurement noise under varying satellite--UE geometry. Under the chosen calibration operating point, false alarms remain controlled in the main elevation operating region, and the event detection rate rises as this bias-to-noise strength increases. Ablation experiments verify the structural contribution of each module. Detection delay and recovery are robust to geometry mismatch and degrade mainly at low signal-to-noise ratio (SNR).
    Protocol-layer security verifies logical identity but cannot directly inspect physical waveform origin. UE-side frequency consistency verification can continuously monitor residual offsets during beam handover without replacing protocol-layer mechanisms, but it strengthens physical-origin consistency as a physical-layer complement for LEO NTN.

    摘要 i Abstract ii 誌謝 iv Contents vi List of Tables ix List of Figures x List of Acronyms xi Chapter 1 Introduction 1 1.1 Research Motivation 1 1.2 Literature Review 1 1.2.1 The Role of Physical-Layer Authentication 1 1.2.2 PLA in LEO: Methods and Challenges 2 1.2.3 Research Gaps and Proposed Approach 2 1.3 Contribution 4 1.4 Thesis Organization 4 Chapter 2 Technical Background 5 2.1 Overview 5 2.2 Intra-Satellite Beam Handover in LEO NTN 6 2.3 UE-Side Handover Operation in NTN 7 2.4 Receiver-Side Frequency Observation Across Handover 7 2.5 Security Relevance of Frequency Continuity 9 Chapter 3 System Model and Problem Formulation 10 3.1 Overview 10 3.2 System Architecture 11 3.3 Propagation and Observation Model 12 3.4 Threat Model 14 3.5 Measurement Noise and Observability 17 3.6 Problem Formulation 18 Chapter 4 Proposed Method 19 4.1 Overview 19 4.2 Receiver-Side Defense Architecture 20 4.3 Residual Formation and Protected Reference 21 4.4 Sequential Detection and FSM Coupling 23 4.5 Parameter Design 25 Chapter 5 Experimental Design and Performance Evaluation 27 5.1 Overview 27 5.2 Experimental Framework 28 5.2.1 Simulation Scenario and Threat Injection 29 5.2.2 Ablation Variants and Baseline Configurations 31 5.2.3 Calibration Protocol and Evaluation Metrics 31 5.3 Geometric Observability Analysis 32 5.3.1 State-Error Dependence of Separability Bias 33 5.3.2 Elevation-Dependent Observability 34 5.4 H0 Residual Validation and Calibration Transfer 35 5.4.1 Null-Residual Behavior under H0 35 5.4.2 False-Alarm Stability under Calibration Transfer 36 5.5 Detection Performance 37 5.5.1 Receiver Operating Characteristic Analysis 37 5.5.2 Detection Rate versus Attack Bias and Observability 38 5.6 Ablation Analysis 39 5.6.1 Role of Observation Stabilization 40 5.6.2 Role of Protected Reference Maintenance 41 5.6.3 Role of Sequential Evidence Accumulation 41 5.7 Sensitivity Analysis 42 5.8 Chapter Summary 43 Chapter 6 Conclusions and Future Work 45 6.1 Conclusions 45 6.2 Limitations and Future Work 47 6.2.1 Research Limitations 47 6.2.2 Future Research Directions 47 References 49

    [1] N. Xie, Z. Li, and H. Tan. A survey of physical-layer authentication in wireless communications. IEEE Communications Surveys & Tutorials, 23(1):282–310, 2021.
    [2] X. Wang, P. Hao, and L. Hanzo. Physical-layer authentication for wireless security enhancement: Current challenges and future developments. IEEE Communications Magazine, 54(6):152–158, 2016.
    [3] O. A. Topal and G. Karabulut Kurt. Physical layer authentication for LEO satellite constellations. In Proc. IEEE Wireless Communications and Networking Conference (WCNC), 2022.
    [4] N. H. S. Suhaimi, N. H. Kamarudin, M. N. A. Khalid, I. Tahir, and M. A. A. Mohamed. State-of-the-art authentication measures in satellite communication networks: A comprehensive analysis. IEEE Access, 12:142241–142264, 2024.
    [5] Q.-Y. Fu, Y.-H. Feng, H.-M. Wang, and P. Liu. Initial satellite access authentication based on Doppler frequency shift. IEEE Wireless Communications Letters, 10(3):498–502, 2021.
    [6] M. Abdrabou and T. A. Gulliver. Authentication for satellite communication systems using physical characteristics. IEEE Open Journal of Vehicular Technology, 4:48–60, 2023.
    [7] M. Abdrabou and T. A. Gulliver. Physical layer authentication for satellite communication systems using machine learning. IEEE Open Journal of the Communications Society, 3:2380–2389, 2022.
    [8] E. Jedermann, M. Strohmeier, M. Schäfer, J. Schmitt, and V. Lenders. Orbit-based authentication using TDOA signatures in satellite networks. In Proc. ACM WiSec, 2021.
    [9] V. Kohli, A. Bhattacharjee, S. Shailendra, and B. Sikdar. EMMA: Ephemeris-assisted LEO inter-satellite link spoof detection dataset and ML framework. IEEE Wireless Communications Letters, 15:2199–2203, 2026.
    [10] G. Oligeri, S. Sciancalepore, S. Raponi, and R. Di Pietro. PAST-AI: Physical-layer authentication of satellite transmitters via deep learning. IEEE Transactions on Information Forensics and Security, 18:274–289, 2023.
    [11] J. Smailes, S. Köhler, M. Birnbach, M. Strohmeier, and I. Martinovic. Watch this space: Securing satellite communication through resilient transmitter fingerprinting. In Proc. ACM CCS, 2023.
    [12] I. Ali, N. Al-Dhahir, and J. E. Hershey. Doppler characterization for LEO satellites. IEEE Transactions on Communications, 46(3):309–313, 1998.
    [13] Y. Guo, J. Wang, K. Geng, Z. Li, F. Li, and L. Fang. SEHAP: Secure and efficient handover authentication protocol in LEO satellite non-terrestrial networks. In Proc. IEEE ICASSP, 2025.
    [14] Q. Kong, R. Lu, and F. Yin. Achieving efficient and secure handover in LEO constellation-assisted beyond 5G networks. IEEE Open Journal of the Communications Society, 3:641–653, 2022.
    [15] Y. Liu, S. Li, Q. Fu, Z. Liu, and Q. Zhou. Analysis of Kalman filter innovation-based GNSS spoofing detection method for INS/GNSS integrated navigation system. IEEE Sensors Journal, 19(13):5167–5178, 2019.
    [16] L. Zhang, H. Zhao, C. Sun, L. Bai, and W. Feng. Enhanced GNSS spoofing detector via multiple-epoch inertial navigation sensor prediction in a tightly-coupled system. IEEE Sensors Journal, 22(9):8633–8646, 2022.
    [17] B. Chen, X. Liu, H. Zhao, and J. C. Principe. Maximum correntropy Kalman filter. Automatica, 76:70–77, 2017.
    [18] 3GPP. NR; NR and NG-RAN Overall Description; Stage 2. Technical Report TS 38.300, 3GPP, 2024.
    [19] 3GPP. NR; Radio Resource Control (RRC); Protocol specification. Technical Report TS 38.331, 3GPP, 2024.
    [20] 3GPP. Solutions for NR to support non-terrestrial networks (NTN). Technical Report TR 38.821, 3GPP, 2020.

    下載圖示
    校外：立即公開
    QR CODE