Utilising K-Means Clustering and Naive Bayes for IoT Anomaly Detection: A Hybrid Approach

被引：0
|
作者：
Best, Lincoln [1 ]
Foo, Ernest [1 ]
Tian, Hui [1 ]
机构：
[1] School of Information and Communication Technology, Griffith University, Brisbane,QLD,4111, Australia
来源：
Smart Sensors, Measurement and Instrumentation | 2022年 / 43卷
关键词：
Compilation and indexing terms; Copyright 2024 Elsevier Inc;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Anomaly detection - Anomaly-detection algorithms - Hybrid approach - K-means - K-means++ clustering - Machine-learning - Multiple devices - Naive bayes - Real-world - Supervised areas
引用
收藏
页码：177 / 214
相关论文
共 50 条
  • [1] Intrusion Detection based on K-Means Clustering and Naive Bayes Classification
    Muda, Z.
    Yassin, W.
    Sulaiman, M. N.
    Udzir, N. I.
    2011 7TH INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY IN ASIA (CITA 11), 2011,
  • [2] An Integration of K-Means Clustering and Naive Bayes Classifier for Intrusion Detection
    Varuna, S.
    Natesan, P.
    2015 3RD INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING, COMMUNICATION AND NETWORKING (ICSCN), 2015,
  • [3] A hybrid approach for anomaly detection using K-means and PSO
    Wang, Ke-Wei
    Qin, Su-Juan
    PROCEEDINGS OF THE 2ND INTERNATIONAL CONFERENCE ON ELECTRONICS, NETWORK AND COMPUTER ENGINEERING (ICENCE 2016), 2016, 67 : 821 - 826
  • [4] An anomaly detection approach based on hybrid differential evolution and K-means clustering in crowd intelligence
    Liu J.
    Liang B.
    Ji W.
    International Journal of Crowd Science, 2021, 5 (02) : 129 - 142
  • [5] ANOMALY-BASED INTRUSION DETECTION THROUGH K-MEANS CLUSTERING AND NAIVES BAYES CLASSIFICATION
    Yassin, Warusia
    Udzir, Nur Izura
    Muda, Zaiton
    Sulaiman, Md. Nasir
    COMPUTING & INFORMATICS, 4TH INTERNATIONAL CONFERENCE, 2013, 2013, : 298 - 303
  • [6] Quantum clustering with k-Means: A hybrid approach
    Poggiali, Alessandro
    Berti, Alessandro
    Bernasconi, Anna
    Del Corso, Gianna M.
    Guidotti, Riccardo
    THEORETICAL COMPUTER SCIENCE, 2024, 992
  • [7] Anomaly based Intrusion Detection using Hybrid Learning Approach of combining k-Medoids Clustering and Naive Bayes Classification
    Chitrakar, Roshan
    Huang Chuanhe
    2012 INTERNATIONAL CONFERENCE ON WIRELESS COMMUNICATIONS, NETWORKING AND MOBILE COMPUTING (WICOM), 2012,
  • [8] A K-Means clustering and SVM based hybrid concept drift detection technique for network anomaly detection
    Jain, Meenal
    Kaur, Gagandeep
    Saxena, Vikas
    EXPERT SYSTEMS WITH APPLICATIONS, 2022, 193
  • [9] An Efficient Hybrid Anomaly Detection Scheme Using K-Means Clustering for Wireless Sensor Networks
    Wazid, Mohammad
    Das, Ashok Kumar
    WIRELESS PERSONAL COMMUNICATIONS, 2016, 90 (04) : 1971 - 2000
  • [10] An Efficient Hybrid Anomaly Detection Scheme Using K-Means Clustering for Wireless Sensor Networks
    Mohammad Wazid
    Ashok Kumar Das
    Wireless Personal Communications, 2016, 90 : 1971 - 2000
12345