Machine learning for cloud security: a systematic review

AB Nassif, MA Talib, Q Nasir, H Albadani… - IEEE …, 2021‏ - ieeexplore.ieee.org
The popularity and usage of Cloud computing is increasing rapidly. Several companies are
investing in this field either for their own use or to provide it as a service for others. One of …

Machine learning techniques for network anomaly detection: A survey

S Eltanbouly, M Bashendy, N AlNaimi… - … on Informatics, IoT …, 2020‏ - ieeexplore.ieee.org
Nowadays, distributed data processing in cloud computing has gained increasing attention
from many researchers. The intense transfer of data has made the network an attractive and …

Machine learning in network anomaly detection: A survey

S Wang, JF Balarezo, S Kandeepan… - IEEe …, 2021‏ - ieeexplore.ieee.org
Anomalies could be the threats to the network that have ever/never happened. To protect
networks against malicious access is always challenging even though it has been studied …

Machine learning for energy-resource allocation, workflow scheduling and live migration in cloud computing: State-of-the-art survey

Y Kumar, S Kaul, YC Hu - Sustainable Computing: Informatics and Systems, 2022‏ - Elsevier
Abstract Machine learning and artificial intelligence techniques have been proven helpful
when pragmatic to a wide range of complex problems and areas such as energy …

TIDCS: A dynamic intrusion detection and classification system based feature selection

Z Chkirbene, A Erbad, R Hamila, A Mohamed… - IEEE …, 2020‏ - ieeexplore.ieee.org
Machine learning techniques are becoming mainstream in intrusion detection systems as
they allow real-time response and have the ability to learn and adapt. By using a …

Cloud-based multiclass anomaly detection and categorization using ensemble learning

F Shahzad, A Mannan, AR Javed, AS Almadhor… - Journal of Cloud …, 2022‏ - Springer
The world of the Internet and networking is exposed to many cyber-attacks and threats. Over
the years, machine learning models have progressed to be integrated into many scenarios …

A review on cybersecurity of cloud computing for supporting connected vehicle applications

MS Salek, SM Khan, M Rahman… - IEEE Internet of …, 2022‏ - ieeexplore.ieee.org
In an Internet of Things (IoT) environment, cloud computing is emerging as a technologically
feasible and economically viable solution for supporting real-time and non-real-time …

Hybrid machine learning for network anomaly intrusion detection

Z Chkirbene, S Eltanbouly, M Bashendy… - … on informatics, IoT …, 2020‏ - ieeexplore.ieee.org
In this paper, a hybrid approach of combing two machine learning algorithms is proposed to
detect the different possible attacks by performing effective feature selection and …

Machine learning based cloud computing anomalies detection

Z Chkirbene, A Erbad, R Hamila, A Gouissem… - IEEE …, 2020‏ - ieeexplore.ieee.org
Recently, machine learning algorithms have been proposed to design new security systems
for anomalies detection as they exhibit fast processing with real-time predictions. However …

AI and soft computing techniques for securing cloud and edge computing: A systematic review

S Hooda, V Lamba, A Kaur - 2021 5th International Conference …, 2021‏ - ieeexplore.ieee.org
In the present work, a systematic map** of various Artificial Intelligence (AI) and Soft
Computing (SC) techniques for cloud and edge computing security has been summarized …