Reliable Identification of IoT Devices from Passive Network Traffic Analysis: Requirements and Recommendations

被引:1
|
作者
Andrews, Ashley [1 ]
Oikonomou, George [1 ]
Armour, Simon [1 ]
Thomas, Paul [1 ]
Cattermole, Thomas [2 ]
机构
[1] Univ Bristol, Bristol, Avon, England
[2] UCL, London, England
关键词
Internet of Things (IoT); Device Identification; Firmware versions; Machine Learning (ML);
D O I
10.1109/WF-IOT58464.2023.10539470
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Internet of Things (IoT) devices are becoming more widespread in networks and can give malicious actors new vectors to compromise networks. Of particular concern are devices running out-of-date firmware versions with known vulnerabilities. Securing real-world IoT networks therefore relies on knowing what devices are on a network and knowing what specific firmware versions they are running. At present, though, commercial solutions that include IoT device identification are not reliable at this level of granularity, and the academic literature has largely ignored the problem. In this paper, we highlight the shortcomings present in current IoT device identification and use these observations to develop a set of lab requirements. We then present our own lab setup for providing reliable real-world IoT device identification that meets this set of requirements. Building on this work, we develop a schema for documenting device versions and event histories that accompany network packet traces as metadata.
引用
收藏
页数:6
相关论文
共 50 条
  • [1] Called Function Identification of IoT Devices by Network Traffic Analysis
    Koike, Daichi
    Ishida, Shigemi
    Arakawa, Yutaka
    36TH ANNUAL ACM SYMPOSIUM ON APPLIED COMPUTING, SAC 2021, 2021, : 737 - 743
  • [2] IoT Devices Discovery and Identification Using Network Traffic Data
    Feng, Yuzhou
    Deng, Liangdong
    Chen, Dong
    PROCEEDINGS OF THE 2019 CONFERENCE ON SECURITY AND PRIVACY IN WIRELESS AND MOBILE NETWORKS (WISEC '19), 2019, : 338 - 339
  • [3] IoT Devices Recognition Through Network Traffic Analysis
    Shahid, Mustafizur R.
    Blanc, Gregory
    Zhang, Zonghua
    Debar, Herve
    2018 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA), 2018, : 5187 - 5192
  • [4] IoTFinder: Efficient Large-Scale Identification of IoT Devices via Passive DNS Traffic Analysis
    Perdisci, Roberto
    Papastergiou, Thomas
    Alrawi, Omar
    Antonakakis, Manos
    2020 5TH IEEE EUROPEAN SYMPOSIUM ON SECURITY AND PRIVACY (EUROS&P 2020), 2020, : 474 - 489
  • [5] Identification of Compromised IoT Devices: Combined Approach Based on Energy Consumption and Network Traffic Analysis
    Jaafar, Fehmi
    Ameyed, Darine
    Barrak, Amine
    Cheriet, Mohamed
    2021 IEEE 21ST INTERNATIONAL CONFERENCE ON SOFTWARE QUALITY, RELIABILITY AND SECURITY (QRS 2021), 2021, : 514 - 523
  • [6] IoT device identification based on network traffic
    Gu, Dinglin
    Zhang, Jian
    Tang, Zhangguo
    Li, Qizhen
    Zhu, Min
    Yan, Hao
    Li, Huanzhou
    WIRELESS NETWORKS, 2025, 31 (02) : 1645 - 1661
  • [7] Network Traffic Characteristics of IoT Devices in Smart Homes
    Mainuddin, Md
    Duan, Zhenhai
    Dong, Yingfei
    30TH INTERNATIONAL CONFERENCE ON COMPUTER COMMUNICATIONS AND NETWORKS (ICCCN 2021), 2021,
  • [8] Identifying IoT Devices Based on Spatial and Temporal Features from Network Traffic
    Yin F.
    Yang L.
    Ma J.
    Zhou Y.
    Wang Y.
    Dai J.
    Security and Communication Networks, 2021, 2021
  • [9] A Framework for Identification and Classification of IoT Devices for Security Analysis in Heterogeneous Network
    Zahid, Hafiz Muhammad
    Saleem, Yasir
    Hayat, Faisal
    Khan, Farrukh Zeeshan
    Alroobaea, Roobaea
    Almansour, Fahad
    Ahmad, Muneer
    Ali, Ihsan
    WIRELESS COMMUNICATIONS & MOBILE COMPUTING, 2022, 2022
  • [10] Identification of Communication Devices from Analysis of Traffic Patterns
    Kawai, Hiroki
    Ata, Shingo
    Nakamura, Nobuyuki
    Oka, Ikuo
    2017 13TH INTERNATIONAL CONFERENCE ON NETWORK AND SERVICE MANAGEMENT (CNSM), 2017,