A survey of intrusion detection in Internet of Things

被引:542
|
作者
Zarpelao, Bruno Bogaz [1 ]
Miani, Rodrigo Sanches [2 ]
Kawakani, Claudio Toshio [1 ]
de Alvarenga, Sean Carlisto [1 ]
机构
[1] State Univ Londrina UEL, Dept Comp Sci, Rodovia Celso Garcia Cid,S-N, BR-86057970 Londrina, Brazil
[2] Univ Fed Uberlandia, Sch Comp Sci FACOM, Uberlandia, MG, Brazil
关键词
Intrusion detection system; Internet of Things; Cybersecurity; DETECTION SYSTEMS; NETWORKS; COMMUNICATION; SECURITY; ENERGY; TRUST;
D O I
10.1016/j.jnca.2017.02.009
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Internet of Things (IoT) is a new paradigm that integrates the Internet and physical objects belonging to different domains such as home automation, industrial process, human health and environmental monitoring. It deepens the presence of Internet-connected devices in our daily activities, bringing, in addition to, many benefits, challenges related to security issues. For more than two decades, Intrusion Detection Systems (IDS) have been an important tool for the protection of networks and information systems. However, applying traditional IDS techniques to IoT is difficult due to its particular characteristics such as constrained-resource devices, specific protocol stacks, and standards. In this paper, we present a survey of IDS research efforts for IoT. Our objective is to identify leading trends, open issues, and future research possibilities. We classified the IDSs proposed in the literature according to the following attributes: detection method, IDS placement strategy, security threat and validation strategy. We also discussed the different possibilities for each attribute, detailing aspects of works that either propose specific IDS schemes for IoT or develop attack detection strategies for IoT threats that might be embedded in IDSs.
引用
收藏
页码:25 / 37
页数:13
相关论文
共 50 条
  • [31] Intrusion detection systems in the Internet of things: A comprehensive investigation
    Hajiheidari, Somayye
    Wakil, Karzan
    Badri, Maryam
    Navimipour, Nima Jafari
    COMPUTER NETWORKS, 2019, 160 : 165 - 191
  • [32] PIDIoT: Probabilistic Intrusion Detection for the Internet-Of-Things
    Zinkus, Maximilian
    Khosmood, Foaad
    DeBruhl, Bruce
    2019 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM), 2019,
  • [33] Intrusion Detection and Prevention in Cloud, Fog, and Internet of Things
    Zhang, Xuyun
    Yuan, Yuan
    Zhou, Zhili
    Li, Shancang
    Qi, Lianyong
    Puthal, Deepak
    SECURITY AND COMMUNICATION NETWORKS, 2019, 2019
  • [34] A comprehensive survey on deep learning-based intrusion detection systems in Internet of Things (IoT)
    Al-Haija, Qasem Abu
    Droos, Ayat
    EXPERT SYSTEMS, 2025, 42 (02)
  • [35] Intrusion detection systems for the internet of things: a probabilistic anomaly detection approach
    Bali, Nadia
    Jaoua, Zied
    Bzeouich, Olfa
    Abbassi, Imed
    International Journal of Computers and Applications, 2024, 46 (11) : 933 - 944
  • [36] An Intrusion Detection System for Denial of Service Attack Detection in Internet of Things
    Lira Melo Sousa, Breno Fabricio
    Abdelouahab, Zair
    Pavao Lopes, Denivaldo Cicero
    Soeiro, Natalia Costa
    Ribeiro, Willian Franca
    PROCEEDINGS OF THE SECOND INTERNATIONAL CONFERENCE ON INTERNET OF THINGS, DATA AND CLOUD COMPUTING (ICC 2017), 2017,
  • [37] Design of Intrusion Detection System for Wormhole Attack Detection in Internet of Things
    Deshmukh-Bhosale, Snehal
    Sonavane, S. S.
    ADVANCED COMPUTING AND INTELLIGENT ENGINEERING, 2020, 1082 : 513 - 523
  • [38] Cluster-based Intrusion Detection Method for Internet of Things
    Choudhary, Sarika
    Kesswani, Nishtha
    2019 IEEE/ACS 16TH INTERNATIONAL CONFERENCE ON COMPUTER SYSTEMS AND APPLICATIONS (AICCSA 2019), 2019,
  • [39] Intrusion Detection Model of Internet of Things Based on Deep Learning
    Wang, Yan
    Han, Dezhi
    Cui, Mingming
    COMPUTER SCIENCE AND INFORMATION SYSTEMS, 2023, 20 (04) : 1519 - 1540
  • [40] Efficient Intrusion Detection System for SDN Orchestrated Internet of Things
    Zeleke, Esubalew M.
    Melaku, Henock M.
    Mengistu, Fikreselam G.
    JOURNAL OF COMPUTER NETWORKS AND COMMUNICATIONS, 2021, 2021