Literature Review of Machine Learning and Threat Intelligence in Cloud Security
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 ca...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10839753/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | 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. |
|---|---|
| ISSN: | 2169-3536 |