Authors :
M. Amshavalli; R. Kishore; S.P. Raguvijay; S. Sri Shyam
Volume/Issue :
Volume 9 - 2024, Issue 4 - April
Google Scholar :
https://tinyurl.com/bde2urfr
Scribd :
https://tinyurl.com/vvs4bxj4
DOI :
https://doi.org/10.38124/ijisrt/IJISRT24APR910
Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.
Abstract :
The use and acceptance of cloud computing are
growing quickly. Numerous businesses are making
investments in this area, either for their own needs or to
offer services to others. The rise of the cloud has led to a
number of security issues for both consumers and
businesses. Machine learning is one method of cloud
security (ML).
ML approaches have been applied in a variety of
ways to stop or identify online threats and security holes.
We present a Systematic Literature Review (SLR) of cloud
security and machine learning approaches and techniques
in this work. After 63 pertinent papers were examined, the
SLR's findings were divided into three primary study
areas: I. The many forms of cloud security
Keywords :
DDOS, Machine Learning, Cloud Security, Privacy, And Security.
The use and acceptance of cloud computing are
growing quickly. Numerous businesses are making
investments in this area, either for their own needs or to
offer services to others. The rise of the cloud has led to a
number of security issues for both consumers and
businesses. Machine learning is one method of cloud
security (ML).
ML approaches have been applied in a variety of
ways to stop or identify online threats and security holes.
We present a Systematic Literature Review (SLR) of cloud
security and machine learning approaches and techniques
in this work. After 63 pertinent papers were examined, the
SLR's findings were divided into three primary study
areas: I. The many forms of cloud security
Keywords :
DDOS, Machine Learning, Cloud Security, Privacy, And Security.