Defending Against DDOS Attacks on IoT Network Throughput: A Trust-Stackelberg Game Model

被引:0
|
作者
Qi, Chunyang [1 ]
Huang, Jie [1 ,2 ]
Huang, Cheng [3 ]
Wu, Huaqing [3 ]
Shen, Xuemin [3 ]
机构
[1] Southeast Univ, Sch Cyber Sci & Engn, Nanjing 211189, Peoples R China
[2] Purple Mt Labs, Nanjing 211111, Peoples R China
[3] Univ Waterloo, Dept Elect & Comp Engn, Waterloo, ON N2L 3G1, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
D O I
10.1109/GLOBECOM48099.2022.10000946
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
IoTs generally rely on resource-constrained devices to sense, relay, and collect data, which are highly vulnerable to Distributed-Denial-of-Services (DDOS) attacks on network throughput. In this paper, we propose a trust-based method to optimize the network throughput of IoTs under DDOS attacks. Specifically, with the assistance of a small number of dedicatedly deployed defense nodes as defenders, a network controller can first measure the behavior of other IoT nodes and categorize them into three types (i.e., innocent, selfish, and attack) through a well-designed trust evaluation model. Then, a Stackelberg game model is constructed accordingly, where defenders are leaders and other nodes are followers. We carefully define the utilities of the leaders and the followers in the game, and transform the optimization problem of the network throughput into the maximization problem of the defenders' utilities considering the utilities of the followers. We adopt the Dinkelbach Programming (DP)-based algorithm to solve the maximization problem such that a Stackelberg equilibrium can be reached with optimized network throughput. Extensive simulations are performed to demonstrate that the proposed defense method can significantly increase the IoT network throughput under different DDOS attack intensities.
引用
收藏
页码:6259 / 6264
页数:6
相关论文
共 50 条
  • [41] A multilevel thrust filtration defending mechanism against DDoS attacks in cloud computing environment
    Iyengar, N. Ch. Sriman Narayana, 1600, Inderscience Enterprises Ltd., 29, route de Pre-Bois, Case Postale 856, CH-1215 Geneva 15, CH-1215, Switzerland (05):
  • [42] A genre trust model for defending shilling attacks in recommender systems
    Li Yang
    Xinxin Niu
    Complex & Intelligent Systems, 2023, 9 : 2929 - 2942
  • [43] Mempool Optimization for Defending Against DDoS Attacks in PoW-based Blockchain Systems
    Saad, Muhammad
    Njilla, Laurent
    Kamhoua, Charles
    Kim, Joongheon
    Nyang, DaeHun
    Mohaisen, Aziz
    2019 IEEE INTERNATIONAL CONFERENCE ON BLOCKCHAIN AND CRYPTOCURRENCY (ICBC), 2019, : 285 - 292
  • [44] A genre trust model for defending shilling attacks in recommender systems
    Yang, Li
    Niu, Xinxin
    COMPLEX & INTELLIGENT SYSTEMS, 2023, 9 (03) : 2929 - 2942
  • [45] A game theoretic defence framework against DoS/DDoS cyber attacks
    Spyridopoulos, T.
    Karanikas, G.
    Tryfonas, T.
    Oikonomou, G.
    COMPUTERS & SECURITY, 2013, 38 : 39 - 50
  • [46] An access control for IoT based on network community perception and social trust against Sybil attacks
    de Oliveira, Gustavo H. C.
    de Souza Batista, Agnaldo
    Nogueira, Michele
    dos Santos, Aldri L.
    INTERNATIONAL JOURNAL OF NETWORK MANAGEMENT, 2022, 32 (01)
  • [47] Defending Against Model Stealing Attacks with Adaptive Misinformation
    Kariyappa, Sanjay
    Qureshi, Moinuddin K.
    2020 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR), 2020, : 767 - 775
  • [48] Mitigating DDoS Flooding Attacks against IoT using Custom Hardware Modules
    Brasilino, Lucas R. B.
    Swany, Martin
    2019 SIXTH INTERNATIONAL CONFERENCE ON INTERNET OF THINGS: SYSTEMS, MANAGEMENT AND SECURITY (IOTSMS), 2019, : 58 - 64
  • [49] Securing IoT Networks Against DDoS Attacks: A Hybrid Deep Learning Approach
    Ul Ain, Noor
    Sardaraz, Muhammad
    Tahir, Muhammad
    Abo Elsoud, Mohamed W.
    Alourani, Abdullah
    SENSORS, 2025, 25 (05)
  • [50] Evidential classification for defending against adversarial attacks on network traffic
    Beechey, Matthew
    Lambotharan, Sangarapillai
    Kyriakopoulos, Konstantinos G.
    INFORMATION FUSION, 2023, 92 : 115 - 126