Novel approach for detection of IoT generated DDoS traffic

被引:50
|
作者
Cvitic, Ivan [1 ]
Perakovic, Dragan [1 ]
Perisa, Marko [1 ]
Botica, Mate [2 ]
机构
[1] Univ Zagreb, Fac Transport & Traff Sci, Vukeliceva 4, Zagreb 10000, Croatia
[2] OiV Transmitters & Commun Ltd, Ul Grada Vukovara 269d, Zagreb 10000, Croatia
关键词
Denial of service; Smart office IoT; Machine learning; Traffic patterns; Traffic features; INTERNET;
D O I
10.1007/s11276-019-02043-1
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The problem of detecting anomalies in network traffic caused by the distributed denial of service (DDoS) attack so far has mainly been investigated in terms of detection of illegitimate DDoS traffic generated by conventional terminal devices (PCs, laptops, mobile devices, tablets, servers). Technological development has resulted in the emergence of the Internet of Things (IoT) concept, whose implementation implies numerous terminal devices with a low level of implemented protection. The large growth and prediction of future growth is noticeable in the environment of a smart home and smart office. IoT devices in such environments are increasingly being used as a platform for generating DDoS traffic due to its numeracy and low level of protection. The aim of this research is to propose a novel approach for detection of DDoS traffic generated by IoT devices in a form of conceptual network anomaly detection model. Proposed conceptual model is based on device classes which are dependent on individual device traffic characteristics.
引用
收藏
页码:1573 / 1586
页数:14
相关论文
共 50 条
  • [21] MBB-IoT: Construction and Evaluation of IoT DDoS Traffic Dataset from a New Perspective
    Qing, Yi
    Liu, Xiangyu
    Du, Yanhui
    CMC-COMPUTERS MATERIALS & CONTINUA, 2023, 76 (02): : 2095 - 2119
  • [22] Timely detection of DDoS attacks in IoT with dimensionality reduction
    Kumari, Pooja
    Jain, Ankit Kumar
    CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS, 2024, 27 (06): : 7869 - 7887
  • [23] A Novel DDoS Floods Detection and Testing Approaches for Network Traffic based on Linux Techniques
    Tahir, Muhammad
    Li, Mingchu
    Ayoub, Naeem
    Shehzaib, Usman
    Wagan, Atif
    INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, 2018, 9 (02) : 341 - 357
  • [24] Detection of DDoS Attack Using SDN in IoT: A Survey
    Pajila, P. J. Beslin
    Julie, E. Golden
    INTELLIGENT COMMUNICATION TECHNOLOGIES AND VIRTUAL MOBILE NETWORKS, ICICV 2019, 2020, 33 : 438 - 452
  • [25] Enhancing DDoS attack detection in IoT using PCA
    Dash, Sanjit Kumar
    Dash, Sweta
    Mahapatra, Satyajit
    Mohanty, Sachi Nandan
    Khan, M. Ijaz
    Medani, Mohamed
    Abdullaev, Sherzod
    Gupta, Manish
    EGYPTIAN INFORMATICS JOURNAL, 2024, 25
  • [26] DDoS attack detection techniques in IoT networks: a survey
    Pakmehr, Amir
    Assmuth, Andreas
    Taheri, Negar
    Ghaffari, Ali
    CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS, 2024, 27 (10): : 14637 - 14668
  • [27] Detection of DDoS Attack in IoT Using Machine Learning
    Kumar, Naveen
    Aleem, Abdul
    Kumar, Sachin
    ADVANCED NETWORK TECHNOLOGIES AND INTELLIGENT COMPUTING, ANTIC 2021, 2022, 1534 : 190 - 199
  • [28] A novel CNN-based approach for detection and classification of DDoS attacks
    Najar, Ashfaq Ahmad
    Sugali, Manohar Naik
    Lone, Faisal Rasheed
    Nazir, Azra
    CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE, 2024, 36 (19):
  • [29] Strengthening network DDOS attack detection in heterogeneous IoT environment with federated XAI learning approach
    Almadhor, Ahmad
    Altalbe, Ali
    Bouazzi, Imen
    Hejaili, Abdullah Al
    Kryvinska, Natalia
    SCIENTIFIC REPORTS, 2024, 14 (01):
  • [30] Detection and Mitigation of DoS and DDoS Attacks in IoT-Based Stateful SDN: An Experimental Approach
    Galeano-Brajones, Jesus
    Carmona-Murillo, Javier
    Valenzuela-Valdes, Juan F.
    Luna-Valero, Francisco
    SENSORS, 2020, 20 (03)