Node State Monitoring Scheme in Fog Radio Access Networks for Intrusion Detection

被引:12
|
作者
An, Xingshuo [1 ]
Lu, Xing [1 ]
Yang, Lei [2 ]
Zhou, Xianwei [1 ]
Lin, Fuhong [1 ]
机构
[1] Univ Sci & Technol Beijing, Sch Comp & Commun Engn, Beijing 100083, Peoples R China
[2] Univ Nevada, Dept Comp Sci & Engn, Reno, NV 89557 USA
基金
美国国家科学基金会; 国家重点研发计划;
关键词
5G; fog computing; IDS; skyline query; node monitoring; FNFS; ARCHITECTURE; INTERNET; SYSTEM; CLOUD;
D O I
10.1109/ACCESS.2019.2899017
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper studies intrusion detection for fog computing in fog radio access networks (F-RANs). As fog nodes are resource constrained, a traditional intrusion detection system (IDS) cannot be directly deployed in F-RANs due to the communication overhead and computational complexity. To address this challenge, we propose a skyline query-based scheme that can analyze the IDS log statistics of fog nodes and provide a complete data processing flow. Specifically, a three-step solution is proposed. First, a lightweight fog node filtering strategy is proposed to filter the raw data, which can reduce the fog-cloud communication overhead. Second, a sliding-window-based mechanism is developed in the cloud server to efficiently process the asynchronous data flow. Then, using the pre-processed data, a set of seriously attacked nodes will be identified by the skyline query. Third, the security threat level of each individual fog node is calculated using the unascertained measure, which can determine the degree of security threat. The numerical simulations show that the proposed scheme can significantly reduce communication overhead and computational complexity.
引用
收藏
页码:21879 / 21888
页数:10
相关论文
共 50 条
  • [41] Access Points Cooperation Based Secretive Coded Caching in Fog Radio Access Networks
    Tan, Qianli
    Jiang, Yanxiang
    Huang, Yige
    Zheng, Fu-Chun
    Niyato, Dusit
    IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2025, 74 (02) : 2826 - 2839
  • [42] Intrusion detection and event monitoring in SCADA networks
    Oman, Paul
    Phillips, Matthew
    CRITICAL INFRASTRUCTURE PROTE CTION, 2008, 253 : 161 - +
  • [43] Deep Learning Based Channel Estimation in Fog Radio Access Networks
    Mao, Zhendong
    Yan, Shi
    CHINA COMMUNICATIONS, 2019, 16 (11) : 16 - 28
  • [44] Fog-Computing-Based Radio Access Networks: Issues and Challenges
    Peng, Mugen
    Yan, Shi
    Zhang, Kecheng
    Wang, Chonggang
    IEEE NETWORK, 2016, 30 (04): : 46 - 53
  • [45] Computation Offloading Analysis in Clustered Fog Radio Access Networks With Repulsion
    Hu, Haonan
    Zhang, Jiliang
    Jiang, Yan
    Li, Zeyang
    Chen, Qianbin
    Zhang, Jie
    IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2021, 70 (10) : 10804 - 10819
  • [46] Interference Coordination for Heterogeneous Users in Asynchronous Fog Radio Access Networks
    Jeon, Sang-Woon
    Jung, Bang Chul
    Lee, Hyungjoo
    Park, Jaedon
    IEEE WIRELESS COMMUNICATIONS LETTERS, 2019, 8 (04) : 1064 - 1068
  • [47] Adaptive Resource Balancing for Serviceability Maximization in Fog Radio Access Networks
    Dao, Nhu-Ngoc
    Lee, Junwook
    Vu, Duc-Nghia
    Paek, Jeongyeup
    Kim, Joongheon
    Cho, Sungrae
    Chung, Ki-Sook
    Keum, Changsup
    IEEE ACCESS, 2017, 5 : 14548 - 14559
  • [48] Joint Optimization of Cloud and Edge Processing for Fog Radio Access Networks
    Park, Seok-Hwan
    Simeone, Osvaldo
    Shitz, Shlomo Shamai
    IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, 2016, 15 (11) : 7621 - 7632
  • [49] Energy Efficient Resource Allocation and Caching in Fog Radio Access Networks
    Zhang, Haijun
    Liu, Xiangnan
    Long, Keping
    Nallanathan, Arumugam
    Leung, Victor C. M.
    2018 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM), 2018,
  • [50] Joint Caching and Multicast for Wireless Fronthaul in Fog Radio Access Networks
    Wei, Xing
    2017 IEEE 86TH VEHICULAR TECHNOLOGY CONFERENCE (VTC-FALL), 2017,