Literature Review of Machine Learning and Threat Intelligence in Cloud Security

被引:0
作者
Thaqi, Rrezearta [1 ]
Krasniqi, Bujar [1 ]
Mazrekaj, Artan [1 ]
Rexha, Blerim [1 ]
机构
[1] Univ Prishtina, Fac Elect & Comp Engn, Pristina 10000, Kosovo
来源
IEEE ACCESS | 2025年 / 13卷
关键词
Cloud computing security; Machine learning; Organizations; Systematic literature review; Scalability; Market research; Protection; Maintenance; Computational modeling; Standards organizations; Cloud computing; security; threat intelligence; machine learning;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Cloud computing has transformed IT services by making them more scalable and cost-effective. However, this shift has also introduced new security challenges that traditional methods are finding hard to tackle. This review paper looks at how combining machine learning (ML) with threat intelligence can improve cloud security - an approach that hasn't been widely explored yet. By reviewing recent studies, we show that ML and threat intelligence does more than detect known threats. They can also adapt to new and evolving ones, making cloud systems more secure against cyberattacks. Our analysis highlights how this combined approach provides better protection and flexibility. We also identify some important gaps in the current research and suggest areas for future study to make these security systems even more effective. This review aims to provide useful insights for researchers, helping to build more proactive cloud security strategies.
引用
收藏
页码:11663 / 11678
页数:16
相关论文
共 74 条
[1]   Enhancing Industrial Cyber Security, Focusing on Formulating a Practical Strategy for Making Predictions through Machine Learning Tools in Cloud Computing Environment [J].
Abbas, Zaheer ;
Myeong, Seunghwan .
ELECTRONICS, 2023, 12 (12)
[2]  
Ahsan M., 2022, J. Cybersecurity Privacy, V2, P527, DOI DOI 10.3390/JCP2030027
[3]   Analysis of adversary activities using cloud-based web services to enhance cyber threat intelligence [J].
Al-Mohannadi, Hamad ;
Awan, Irfan ;
Al Hamar, Jassim .
SERVICE ORIENTED COMPUTING AND APPLICATIONS, 2020, 14 (03) :175-187
[4]   Effective Intrusion Detection System to Secure Data in Cloud Using Machine Learning [J].
Aldallal, Ammar ;
Alisa, Faisal .
SYMMETRY-BASEL, 2021, 13 (12)
[5]   Hypervisor-based cloud intrusion detection through online multivariate statistical change tracking [J].
Aldribi, Abdulaziz ;
Traore, Issa ;
Moa, Belaid ;
Nwamuo, Onyekachi .
COMPUTERS & SECURITY, 2020, 88
[6]   Rapid detection of sunset yellow adulteration in tea powder with variable selection coupled to machine learning tools using spectral data [J].
Amsaraj, Rani ;
Mutturi, Sarma .
JOURNAL OF FOOD SCIENCE AND TECHNOLOGY-MYSORE, 2023, 60 (05) :1530-1540
[7]   Insider Attack Detection Using Deep Belief Neural Network in Cloud Computing [J].
Anakath, A. S. ;
Kannadasan, R. ;
Joseph, Niju P. ;
Boominathan, P. ;
Sreekanth, G. R. .
COMPUTER SYSTEMS SCIENCE AND ENGINEERING, 2022, 41 (02) :479-492
[8]  
[Anonymous], [14] "What Is Data Visualization? Definition, Examples, And Learning Resources," Tableau. Accessed: Jan. 24, 2023. [Online]. Available: https://www.tableau.com/learn/articles/data-visualization
[9]  
[Anonymous], [11] Intel Corporation, [online]. Available: https://www.intel.com/content/www/us/en/content-details/755315/ accelerate-deep-learning-training-with-habana-gaudi-ai-processor-and-ddn-ai html, [Accessed: Oct-20-2023].
[10]  
[Anonymous], WHAT IS AMAZON VPC A