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Intelligent Data Engineering and Analytics pp 41–50Cite as

SAGRU: A Stacked Autoencoder-Based Gated Recurrent Unit Approach to Intrusion Detection

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1177))

Abstract

The ubiquitous use of the Internet in today’s technological world makes the computer systems prone to cyberattacks. This led to the emergence of Intrusion Detection System (IDS). Nowadays, IDS can be built using deep learning approaches. The issues in the existing deep learning-based IDS are the curse of dimensionality and vanishing gradient problems leading to high learning time and low accuracy. In this paper, a Stacked Autoencoder-based Gated Recurrent Unit (SAGRU) approach has been proposed to overcome these issues by extracting the relevant features by reducing the dimension of the data using Stacked Autoencoder (SA) and learning the extracted features using Gated Recurrent Unit (GRU) to construct the IDS. Experiments were conducted on NSL KDD network traffic dataset and it is evident that the proposed SAGRU approach provides promising results with low learning time and high accuracy as compared to the existing deep learning approaches.

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References

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Authors and Affiliations

  1. National Institute of Technology, Tiruchirappalli, 620 015, Tamil Nadu, India

    N. G. Bhuvaneswari Amma, S. Selvakumar & R. Leela Velusamy

  2. Indian Institute of Information Technology, Una, 177 209, Himachal Pradesh, India

    S. Selvakumar

Authors
  1. N. G. Bhuvaneswari Amma
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  2. S. Selvakumar
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  3. R. Leela Velusamy
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Corresponding author

Correspondence to N. G. Bhuvaneswari Amma .

Editor information

Editors and Affiliations

  1. School of Computer Engineering, Kalinga Institute Industrial Technology, Bhubaneswar, Odisha, India

    Suresh Chandra Satapathy

  2. Department of Informatics, University of Leicester, Leicester, UK

    Yu-Dong Zhang

  3. Department of Electronics and Communication Engineering, Shri Ramswaroop Memorial Group of Professional Colleges (SRMGPC), Lucknow, Uttar Pradesh, India

    Vikrant Bhateja

  4. School of Management, National Institute of Technology Karnataka, Surathkal, Karnataka, India

    Ritanjali Majhi

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Bhuvaneswari Amma, N.G., Selvakumar, S., Leela Velusamy, R. (2021). SAGRU: A Stacked Autoencoder-Based Gated Recurrent Unit Approach to Intrusion Detection. In: Satapathy, S., Zhang, YD., Bhateja, V., Majhi, R. (eds) Intelligent Data Engineering and Analytics. Advances in Intelligent Systems and Computing, vol 1177. Springer, Singapore. https://doi.org/10.1007/978-981-15-5679-1_5

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