Deakin University
Browse

File(s) under permanent embargo

A sparse protocol parsing method for IIoT protocols based on HMM hybrid model

conference contribution
posted on 2020-01-01, 00:00 authored by Yunhua He, Jialong Shen, Ke Xiao, Keshav SoodKeshav Sood, Chao Wang, Limin Sun
As the intelligentization of Industrial Internet of Things (IIoT) broke the relatively closed and credible industrial environment, IIoT faces increasingly serious security problems. The commonly used vulnerability discovery method is protocol reverse engineering. However, it is difficult to analyze IIoT protocols with existing protocol reverse engineering approaches, as they influence the normal operation or have spare sample data. In this paper, a sparse protocol parsing method for IIoT protocols is proposed. The parsing method expands the samples of the captured IIoT protocol message sequences using a genetic algorithm (GA), which designs its fitness function based on the protocol response data to select high-quality samples. By combining the GA with the hidden Markov model (HMM) with lower algorithm complexity, a hybrid parsing model is constructed to improve accuracy in a gradual evolution way. Through comparison experiments on various IIoT protocols, our HMM hybrid model has better performance than RNN hybrid models under sparse samples.

History

Pagination

1-6

Location

Online, Ireland

Start date

2020-06-07

End date

2020-06-11

ISBN-13

978-1-7281-5089-5

Language

eng

Publication classification

E1 Full written paper - refereed

Editor/Contributor(s)

[Unknown]

Title of proceedings

ICC 2020 : Proceedings of the 2020 IEEE International Conference on Communications

Event

IEEE Communications Society. International Conference (2020 : Online, Ireland)

Publisher

Institute of Electrical and Electronics Engineers

Place of publication

Piscataway, N.J.

Series

IEEE Communications Society International Conference

Usage metrics

    Research Publications

    Categories

    No categories selected

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC