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研究生： 黃騰加
Teng-Chia Huang
論文名稱： 軟體定義車內網路之K平均演算法偵測減緩分散式阻斷服務攻擊
K-­means Detection and Alleviation to DDoS Attack in Software­-Defined In­-Vehicle Networks
指導教授： 黃琴雅
Chin-Ya Huang
口試委員: 陳彥宏
Yen-Hung Chen
沈上翔
Shan-Hsiang Shen
金台齡
Tai-Lin Chin
學位類別： 碩士
Master
系所名稱： 電資學院 - 電子工程系
Department of Electronic and Computer Engineering
論文出版年： 2021
畢業學年度： 110
語文別： 英文
論文頁數： 94
中文關鍵詞： 軟體定義網路 、分散式阻斷服務攻擊 、自動車 、機器學習
外文關鍵詞： Software-Defined Networks, Distrubuted Denial-of-Service, Autonomous Vehicle, Machine Learning
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    • Recommendation Letter. . . . . . . . . . . . . . . . . . . . . . . . i Approval Letter . . . . . . . . . . . . . . . . . . . . . . . . . . ii Abstract in Chinese. . . . . . . . . . . . . . . . . . . . . . . . iii Abstract in English . . . . . . . . . . . . . . . . . . . . . . . . iv Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . v Contents. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vi List of Figures. . . . . . . . . . . . . . . . . . . . . . . . . . ix List of Tables. . . . . . . . . . . . . . . . . . . . . . . . . . xiv List of Algorithms. . . . . . . . . . . . . . . . . . . . . . . . . xv 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 2 Background and Related Works . . . . . . . . . . . . . . . . . . . 7 2.1 In­Vehicle Network Protocols. . . . . . . . . . . . . . . . . . . 7 2.2 Sensors. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 2.3 SDN networks . . . . . . . . . . . . . . . . . . . . . . . . . . 9 2.4 Other devices. . . . . . . . . . . . . . . . . . . . . . . . . . 9 2.5 Existing Solutions. . . . . . . . . . . . . . . . . . . . . . . 10 3 System model. . . . . . . . . . . . . . . . . . . . . . . . . . . 13 3.1 Network topology. . . . . . . . . . . . . . . . . . . . . . . . 13 3.2 Problem formulation . . . . . . . . . . . . . . . . . . . . . . 16 3.3 Attack Model. . . . . . . . . . . . . . . . . . . . . . . . . . 18 4 K­means Detection and Alleviation (KDA). . . . . . . . . . . . . . 19 4.1 Overview. . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 4.2 Data collection module. . . . . . . . . . . . . . . . . . . . . 21 4.3 Detection module. . . . . . . . . . . . . . . . . . . . . . . . 22 4.4 Alleviation module. . . . . . . . . . . . . . . . . . . . . . . 23 4.5 Recovery module . . . . . . . . . . . . . . . . . . . . . . . . 24 4.6 Limitation. . . . . . . . . . . . . . . . . . . . . . . . . . . 25 4.7 Implementation. . . . . . . . . . . . . . . . . . . . . . . . . 25 5 Evaluation. . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 5.1 Performance . . . . . . . . . . . . . . . . . . . . . . . . . . 29 5.1.1 One Attacker. . . . . . . . . . . . . . . . . . . . . . . . . 29 5.1.2 Two Attackers . . . . . . . . . . . . . . . . . . . . . . . . 36 5.1.3 Three Attackers . . . . . . . . . . . . . . . . . . . . . . . 42 5.1.4 Four Attackers . . . . . . . . . . . . . . . . . . . . . . . 47 5.1.5 Five Attackers. . . . . . . . . . . . . . . . . . . . . . . . 52 5.1.6 Six Attackers . . . . . . . . . . . . . . . . . . . . . . . . 57 5.1.7 Seven Attackers . . . . . . . . . . . . . . . . . . . . . . . 62 5.2 Threshold setting . . . . . . . . . . . . . . . . . . . . . . . 67 5.3 Detection Accuracy. . . . . . . . . . . . . . . . . . . . . . . 70 6 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . 75 6.1 Future Work . . . . . . . . . . . . . . . . . . . . . . . . . . 75 References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76 Letter of Authority . . . . . . . . . . . . . . . . . . . . . . . . 78

    [1] Requirements Network(n.d.), “Network requirements for video conferencing.” [Online]. Available: http://www.requirementsnetwork.com/video­conferencing.htm. [Accessed Jul. 3, 2021].
    [2] R. Tandon, “A survey of distributed denial of service attacks and defenses,” arXiv:2008.01345[cs.CR], Aug. 2020.
    [3] P. Richards, “What type of computer do i need to live stream.” Mar. 2021. [Online]. Available: https://streamgeeks.us/what­computer­do­i­need­to­live­stream/. [Accessed Jul. 3, 2021].
    [4] R. Doriguzzi­Corin, S. Millar, S. Scott­Hayward, J. Martínez­del Rincón, and D. Siracusa, “Lucid: A practical, lightweight deep learning solution for ddos attack detection,” IEEE Transactions on Network and Service Management, vol. 17, pp. 876–889, Feb. 2020.
    [5] D. F. Macedo, D. Guedes, L. F. M. Vieira, M. A. M. Vieira, and M. Nogueira, “Programmable networks-from software­-defined radio to software-­defined networking,” IEEE Communications Survey Tutorials, vol. 17, pp. 1102–1125, Feb. 2015.
    [6] Y. Qin, J. Wei, and W. Yang, “Deep learning based anomaly detection scheme in software-­defined networking,” in Proc. 20th Asia­Pacific Netw. Operations Manage. Symp. (APNOMS), pp. 1–4, Sep. 2019.
    [7] Y. Xu and Y. Liu, “DDoS attack detection under SDN context,” in Proc. 35th Annual IEEE Int. Conf. Comput. Commun. (INFOCOM), pp. 1–9, Apr. 2016.
    [8] G. de Biasi, L. F. M. Vieira, and A. A. F. Loureiro, “Sentinel: Defense mechanism against DDoS flooding attack in software defined vehicular network,” in Proc. IEEE Int. Conf. Commun. (ICC), pp. 1–6, May 2018.
    [9] R. Xie, M. Xu, J. Cao, and W. Li, “Softguard: Defense against the low­rate TCP attack in SDN,” in Proc. IEEE Int. Conf. Commun. (ICC), pp. 1–6, May 2019.
    [10] K. Hong, Y. Kim, H. Choi, and J. Park, “SDN­-assisted slow HTTP DDoS attack defense method,” IEEE Communications Letters, vol. 22, pp. 688–691, Apr. 2018.
    [11] S. Gao, Z. Peng, B. Xiao, A. Hu, Y. Song, and K. Ren, “Detection and mitigation of DoS attacks in software defined networks,” IEEE/ACM Transactions on Networking, vol. 28, pp. 1419–1433, Jun. 2020.
    [12] M. Yue, H. Wang, L. Liu, and Z. Wu, “Detecting DoS attacks based on multi­features in SDN,” IEEE Access, vol. 8, pp. 104688–104700, Jun. 2020.
    [13] P. Droździel, S. Tarkowski, I. Rybicka, and R. Wrona, “Drivers’ reaction time research in the conditions in the real traffic,” Open Engineering, vol. 10, pp. 35–47, Jan. 2020.
    [14] S. Dmitriev, “Autonomous cars will generate more than 300TB of data per year.” Jul. 2020. [Online].Available: https://www.tuxera.com/blog/autonomous­cars­300­tb­of­data­per­year/. [Accessed Jul. 3, 2020].
    [15] J. Huang, M. Zhao, Y. Zhou, and C. Xing, “In­-vehicle networking: Protocols, challenges, and solutions,” IEEE Network, vol. 33, pp. 92–98, Jan. 2019.
    [16] F. Rosique, P. J. Navarro, C. Fernández, and A. Padilla, “A systematic review of perception system and simulators for autonomous vehicles research,” Sensors, vol. 19, p. 648, Feb. 2019.
    [17] N. Ravi and S. M. Shalinie, “Learning-­driven detection and mitigation of DDoS attack in IoT via SDN-­cloud architecture,” IEEE Internet of Things Journal, vol. 7, pp. 3559–3570, Apr. 2020.
    [18] A. Shafer, “Udp vs. tcp and which one to use for video streaming.” Dec. 16, 2020. [Online]. Available: https://www.wowza.com/blog/udp­vs­tcp. [Accessed Mar. 3, 2021].
    [19] Open Networking Foundation, “OpenFlow switch specification.” Jun. 25, 2012. [Online]. Available: https://opennetworking.org/wp­content/uploads/2014/10/openflow­spec­v1.3.0.pdf. [Accessed Jul. 10, 2018].
    [20] Nippon Telegraph and Telephone Corporation(n.d.), “Welcome to ryu the network operating system(nos).” [Online]. Available: https://ryu­sdn.org/. [Accessed Jul. 10, 2018].
    [21] B. Lantz, B. Heller, and N. Mckeown, “A network in a laptop: Rapid prototyping for software­-defined networks,” in Proc. of the 9th ACM SIGCOMM Workshop on Hot Topics in Networks, pp. 19:1–19:6, Oct. 2010.
    [22] N. Ravi, S. M. Shalinie, and D. D. J. Theres, “Balance: Link flooding attack detection and mitigation via hybrid-­SDN,” IEEE Transactions on Network and Service Management, vol. 17, pp. 1715–1729, Sept. 2020.

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