Challenges and Opportunities of Autonomous Cyber Defence (ACyD) Against Cyber Attacks

Michael Oreyomi, Hamid Jahankhani*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

4 Citations (Scopus)

Abstract

The exponential growth of Autonomous Intelligent Malware (AIM) has really changed the landscape in the cyber security fight against that attack of auto generated threats and how these threats needs to be dealt with. This research focuses on the use of Artificial Intelligence (AI), Machine learning (ML) and Deep learning (DL) to mitigate auto-generated cyber attacks which are hard to track and neutralise. Hence, the key issue that the research proposes to address is to evaluate the key challenges in using AI and ML as decision tools against autonomous cyber attacks, and the opportunities it presents. A proposal is posited on the future utilisation of Autonomous Cyber Defence (ACyD) as a tool to neutralise Autonomous intelligent Malware (AIM), embedded into Security Information and Events Management systems (SIEM). ACyD is principally a self-defending and self-healing cyber security system with the sole aim of persistently and autonomously defending all cyber physical systems against cyber attacks. The use of ACyD in cyber defence is a relatively new research area that the author hopes will gain grounds in the future.

Original languageEnglish
Title of host publicationBlockchain and Other Emerging Technologies for Digital Business Strategies
EditorsHamid Jahankhani, David V. Kilpin, Stefan Kendzierskyj
Place of PublicationCham, Switzerland
PublisherSpringer
Pages239-269
Number of pages31
Edition1st
ISBN (Electronic)9783030982256
ISBN (Print)9783030982249, 9783030982270
DOIs
Publication statusPublished - 4 May 2022
Externally publishedYes

Publication series

NameAdvanced Sciences and Technologies for Security Applications (ASTSA)
PublisherSpringer
ISSN (Print)1613-5113
ISSN (Electronic)2363-9466

Keywords

  • ACyD
  • Artificial intelligence (AI)
  • Autonomous cyber defence
  • C4ISR
  • Convolutional neural network (CNN)
  • Cyber attack
  • Cyber defence
  • Deep autoencoder (DAE)
  • Deep learning (DL)
  • Machine learning (ML)

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