Cyber security systems have become of ground zero importance at all levels, inclusive of
data, host, network, and application levels. Cyber security refers to a combination of …

University of Zimbabwe Abstract-The purpose of the research is to evaluate Machine
Learning and Big Data Analytics paradigms for use in Cybersecurity. Cybersecurity refers to …

In a computing context, cybersecurity is undergoing massive shifts in technology and its
operations in recent days, and data science is driving the change. Extracting security …

This book is intended to present the state of the art in research on machine learning and big
data analytics. The accepted chapters covered many themes including artificial intelligence …

Deep learning techniques have shown significant impact in enhancing security across
various domains by leveraging artificial neural networks models. When applied to cloud …

Deep learning and machine learning show effectiveness in identifying and addressing cloud
security threats. Despite the large number of articles published in this field, there remains a …

The use of machine learning has become widespread across various fields because of its
superior performance compared to conventional rule-based algorithms. As a result, these …

The technological and social changes in the current information age pose new challenges
for security analysts. To overcome these challenges, new strategies and security solutions …

This book addresses the key security challenges in the big data centric computing and
network systems, and discusses how to tackle them using a mix of conventional and state-of …

The previous ten years have seen a rise in computer use, which has also led to an increase
in the size of cyber attacks. Because the majority of computers are networked, they are …