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

研究成果: 書籍/レポート タイプへの寄稿会議への寄与

2 被引用数 (Scopus)

抄録

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.

本文言語英語
ホスト出版物のタイトルScience of Cyber Security - SciSec 2022 Workshops - AI-CryptoSec, TA-BC-NFT, and MathSci-Qsafe 2022, Revised Selected Papers
編集者Chunhua Su, Kouichi Sakurai
出版社Springer Science and Business Media Deutschland GmbH
ページ196-212
ページ数17
ISBN(印刷版)9789811977688
DOI
出版ステータス出版済み - 2022
イベントAI 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, 日本
継続期間: 8月 10 20228月 12 2022

出版物シリーズ

名前Communications in Computer and Information Science
1680 CCIS
ISSN(印刷版)1865-0929
ISSN(電子版)1865-0937

会議

会議AI 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
国/地域日本
CityMatsue
Period8/10/228/12/22

!!!All Science Journal Classification (ASJC) codes

  • コンピュータサイエンス一般
  • 数学一般

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