Artificial intelligence algorithms for cyberspace security applications: a technological and status review

Jie CHEN; Dandan WU; Ruiyun XIE

doi:10.1631/FITEE.2200314

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Artificial intelligence algorithms for cyberspace security applications: a technological and status review

Regular Papers | Updated：2023-08-29

- Artificial intelligence algorithms for cyberspace security applications: a technological and status review
  Enhanced Publication
- 人工智能算法在网络空间安全中的应用：技术与现状综述
- Frontiers of Information Technology & Electronic Engineering Vol. 24, Issue 8, Pages: 1117-1142(2023)
- Affiliations：
  
  1.School of Cybersecurity, Northwestern Polytechnical University, Xi'an 710000, China
  2.China Electronics Technology Network Information Security Co., Ltd., Chengdu 610000, China
- Author bio：
  
  ‡Corresponding author
  wudd@cetcsc.com
- Funds：
- DOI：10.1631/FITEE.2200314
  CLC： TP393.08
- Published：0 August 2023，
  
  Received：21 July 2022，
  
  Revised：11 December 2022，
- Accepted：
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JIE CHEN, DANDAN WU, RUIYUN XIE. Artificial intelligence algorithms for cyberspace security applications: a technological and status review. [J]. Frontiers of information technology & electronic engineering, 2023, 24(8): 1117-1142.
DOI：

JIE CHEN, DANDAN WU, RUIYUN XIE. Artificial intelligence algorithms for cyberspace security applications: a technological and status review. [J]. Frontiers of information technology & electronic engineering, 2023, 24(8): 1117-1142. DOI： 10.1631/FITEE.2200314.

摘要

网络空间安全急需解决的3个技术问题是：网络攻击检测的及时性和准确性、安全态势的可信评估和预测以及安全防御策略优化的有效性。人工智能算法已成为网络安全应用增加安全机会和提高对抗能力的核心手段。近年来，人工智能技术的突破和应用为提高网络防御能力提供了先进的技术支持。本综述对2017至2022年间人工智能技术在网络空间安全领域的最新应用进行了全面回顾。参考文献来源于各种期刊和会议，其中52.68%的论文来自Elsevier、Springer和IEEE期刊，25%来自国际学术会议。本综述重点介绍了机器学习、深度学习和一些流行的优化算法在该领域的最新应用进展，对算法模型的特点、性能结果、数据集、以及潜在的优点和局限性进行了分析，强调了现存的挑战。本工作旨在为想进一步挖掘人工智能技术在网络空间安全领域应用的潜力、解决特定网络空间安全问题的研究人员提供技术指导，掌握当前技术和应用的发展趋势以及网络安全领域的热点问题。同时，本综述对当前面临的挑战提供了有效应对策略和方向。

Abstract

Three technical problems should be solved urgently in cyberspace security: the timeliness and accuracy of network attack detection

the credibility assessment and prediction of the security situation

and the effectiveness of security defense strategy optimization. Artificial intelligence (AI) algorithms have become the core means to increase the chance of security and improve the network attack and defense ability in the application of cyberspace security. Recently

the breakthrough and application of AI technology have provided a series of advanced approaches for further enhancing network defense ability. This work presents a comprehensive review of AI technology articles for cyberspace security applications

mainly from 2017 to 2022. The papers are selected from a variety of journals and conferences: 52.68% are from Elsevier

Springer

and IEEE journals and 25% are from international conferences. With a specific focus on the latest approaches in machine learning (ML)

deep learning (DL)

and some popular optimization algorithms

the characteristics of the algorithmic models

performance results

datasets

potential benefits

and limitations are analyzed

and some of the existing challenges are highlighted. This work is intended to provide technical guidance for researchers who would like to obtain the potential of AI technical methods for cyberspace security and to provide tips for the later resolution of specific cyberspace security issues

and a mastery of the current development trends of technology and application and hot issues in the field of network security. It also indicates certain existing challenges and gives directions for addressing them effectively.

关键词

人工智能机器学习深度学习优化算法混合算法网络空间安全

Keywords

Artificial intelligence (AI)Machine learning (ML)Deep learning (DL)Optimization algorithmHybrid algorithmCyberspace security

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