In machine learning, the data imbalance imposes challenges to perform data analytics in
almost all areas of real-world research. The raw primary data often suffers from the skewed …

Anomaly detection is concerned with identifying data patterns that deviate remarkably from
the expected behavior. This is an important research problem, due to its broad set of …

In the present world huge amounts of data are stored and transferred from one location to
another. The data when transferred or stored is primed exposed to attack. Although various …

In order to meet stringent performance requirements, system administrators must effectively
detect undesirable performance behaviours, identify potential root causes, and take …

Anomaly detection is a critical task for maintaining the performance of a cloud system. Using
data-driven methods to address this issue is the mainstream in recent years. However, due …

Today, machine learning and deep learning have paved the way for vital and critical
applications such as abnormal detection. Despite the modernity of transfer learning, it has …

The orchestration of cloud computing infrastructures is challenging, considering the number,
heterogeneity and dynamicity of the involved resources, along with the highly distributed …

Abrupt development of resources and rising expenses of infrastructure are leading
institutions to take on cloud computing. Albeit, the cloud environment is vulnerable to various …

Advancements in cloud technologies have increased the infrastructural needs of data
centers due to storage needs and processing of extensive dimensional data. Many service …

Despite employing the architectures designed for high service reliability and availability,
cloud computing systems do experience service outages and performance slowdown. In …