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Introduction

  • Kwangjo Kim
  • Muhamad Erza Aminanto
  • Harry Chandra Tanuwidjaja
Chapter
  • 1.5k Downloads
Part of the SpringerBriefs on Cyber Security Systems and Networks book series (BRIEFSCSSN)

Abstract

This chapter discusses the importance of IDS in computer networks while wireless networks grow rapidly these days by providing a survey of a security breach in wireless networks. Many methods have been used to improve IDS performance, the most promising one is to deploy machine learning. Then, the usefulness of recent models of machine learning, called a deep learning, is highlighted to improve IDS performance, particularly as a Feature Learning (FL) approach. We also explain the motivation of surveying deep learning-based IDSs.

Keywords

Intrusion Detection System (IDS) Deep Learning Methods Stacked Denoising Auto-encoder (SDAE) Ransomware Deep Boltzmann Machine (DBM) 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd., part of Springer Nature 2018

Authors and Affiliations

  • Kwangjo Kim
    • 1
  • Muhamad Erza Aminanto
    • 1
  • Harry Chandra Tanuwidjaja
    • 1
  1. 1.School of Computing (SoC)Korea Advanced Institute of Science and TechnologyDaejeonKorea (Republic of)

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