Advances in Adversarial Attacks and Defenses in Intrusion Detection System: A Survey

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

Machine learning is one of the predominant methods used in computer science and has been widely and successfully applied in many areas such as computer vision, pattern recognition, natural language processing, cyber security etc. In cyber security, the application of machine learning algorithms for network intrusion detection system (NIDS) has seen promising results for anomaly detection mostly with the adoption of deep learning and is still growing. However, machine learning algorithms are vulnerable to adversarial attacks resulting in significant performance degradation. Adversarial attacks are security threats that aim to deceive the learning algorithm by manipulating its predictions, and Adversarial machine learning is a research area that studies both the generation and defense of such attacks. Researchers have extensively worked on the adversarial machine learning in computer vision but not many works in Intrusion detection system. However, failure in this critical Intrusion detection area could compromise the security of an entire system, and need much attention. This paper provides a review of the advancement in adversarial machine learning based intrusion detection and explores the various defense techniques applied against. Finally discuss their limitations for future research direction in this emerging area.

Original languageEnglish
Title of host publicationScience of Cyber Security - SciSec 2022 Workshops - AI-CryptoSec, TA-BC-NFT, and MathSci-Qsafe 2022, Revised Selected Papers
EditorsChunhua Su, Kouichi Sakurai
PublisherSpringer Science and Business Media Deutschland GmbH
Pages196-212
Number of pages17
ISBN (Print)9789811977688
DOIs
Publication statusPublished - 2022
EventAI Crypto and Security Workshop, AI-CryptoSec 2022, Theory and Application of Blockchain and NFT Workshop, TA-BC-NFT 2022, and Mathematical Science of Quantum Safety and its Application Workshop, MathSci-Qsafe 2022 held in conjunction with 4th International Conference on Science of Cyber Security Workshops, SciSec 2022 - Matsue, Japan
Duration: Aug 10 2022Aug 12 2022

Publication series

NameCommunications in Computer and Information Science
Volume1680 CCIS
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937

Conference

ConferenceAI Crypto and Security Workshop, AI-CryptoSec 2022, Theory and Application of Blockchain and NFT Workshop, TA-BC-NFT 2022, and Mathematical Science of Quantum Safety and its Application Workshop, MathSci-Qsafe 2022 held in conjunction with 4th International Conference on Science of Cyber Security Workshops, SciSec 2022
Country/TerritoryJapan
CityMatsue
Period8/10/228/12/22

All Science Journal Classification (ASJC) codes

  • General Computer Science
  • General Mathematics

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