Deep Learning Approaches to Cloud Security: Deep Learning Approaches for Cloud Security

✍ Scribed by Pramod Singh Rathore (editor), Vishal Dutt (editor), Rashmi Agrawal (editor), Satya Murthy Sasubilli (editor), Srinivasa Rao Swarna (editor)

Publisher: Wiley-Scrivener
Year: 2022
Tongue: English
Leaves: 304
Edition: 1
Category: Library

⬇ Acquire This Volume

No coin nor oath required. For personal study only.

✦ Synopsis

DEEP LEARNING APPROACHES TO CLOUD SECURITY

Covering one of the most important subjects to our society today, cloud security, this editorial team delves into solutions taken from evolving deep learning approaches, solutions allowing computers to learn from experience and understand the world in terms of a hierarchy of concepts, with each concept defined through its relation to simpler concepts.

Deep learning is the fastest growing field in computer science. Deep learning algorithms and techniques are found to be useful in different areas like automatic machine translation, automatic handwriting generation, visual recognition, fraud detection, and detecting developmental delay in children. However, applying deep learning techniques or algorithms successfully in these areas needs a concerted effort, fostering integrative research between experts ranging from diverse disciplines from data science to visualization. This book provides state of the art approaches of deep learning in these areas, including areas of detection and prediction, as well as future framework development, building service systems and analytical aspects. In all these topics, deep learning approaches, such as artificial neural networks, fuzzy logic, genetic algorithms, and hybrid mechanisms are used. This book is intended for dealing with modeling and performance prediction of the efficient cloud security systems, thereby bringing a newer dimension to this rapidly evolving field.

This groundbreaking new volume presents these topics and trends of deep learning, bridging the research gap, and presenting solutions to the challenges facing the engineer or scientist every day in this area. Whether for the veteran engineer or the student, this is a must-have for any library.

Deep Learning Approaches to Cloud Security:

Is the first volume of its kind to go in-depth on the newest trends and innovations in cloud security through the use of deep learning approaches
Covers these important new innovations, such as AI, data mining, and other evolving computing technologies in relation to cloud security
Is a useful reference for the veteran computer scientist or engineer working in this area or an engineer new to the area, or a student in this area
Discusses not just the practical applications of these technologies, but also the broader concepts and theory behind how these deep learning tools are vital not just to cloud security, but society as a whole

Audience: Computer scientists, scientists and engineers working with information technology, design, network security, and manufacturing, researchers in computers, electronics, and electrical and network security, integrated domain, and data analytics, and students in these areas

📜 SIMILAR VOLUMES

Deep Learning Approaches to Cloud Securi

📁 Deep Learning Approaches to Cloud Security: Deep Learning Approaches for Cloud Security

✍ Pramod Singh Rathore (editor), Vishal Dutt (editor), Rashmi Agrawal (editor), Sa 📂 Library 📅 2022 🏛 Wiley-Scrivener 🌐 English

DEEP LEARNING APPROACHES TO CLOUD SECURITY Covering one of the most important subjects to our society today, cloud security, this editorial team delves into solutions taken from evolving deep learning approaches, solutions allowing computers to learn from experience and understand

Deep Learning Approaches for Security Th

📁 Deep Learning Approaches for Security Threats in IoT Environments

✍ Mohamed Abdel-Basset, Nour Moustafa, Hossam Hawash 📂 Library 📅 2022 🏛 Wiley-IEEE Press 🌐 English

Deep Learning Approaches for Security Threats in IoT EnvironmentsAn expert discussion of the application of deep learning methods in the IoT security environmentIn Deep Learning Approaches for Security Threats in IoT Environments, a

A Deep Learning based Approach to Proac

📁 A Deep Learning based Approach to Proactive and Reactive Enterprise Security

✍ Sumit Chakraborty 📂 Library 📅 2015 🏛 Business Analytics Research Lab India 🌐 English

Abstract: This work presents the construction of a deep learning based algorithmic mechanism to ensure the security of an information system based on proactive and reactive approach. The basic building blocks of the mechanism are threat analytics, cryptographic solutions and adaptive secure multipar

Securing Cloud Services - A Pragmatic Ap

📁 Securing Cloud Services - A Pragmatic Approach to Security Architecture in the Cloud

✍ Newcombe, Lee 📂 Library 📅 2012 🏛 IT Governance Publishing

This book provides an overview of security architecture processes and explains how they may be used to derive an appropriate set of security controls to manage the risks associated with working in the Cloud. Part 1 introduces Cloud Computing and describes the main service models (IaaS, PaaS and SaaS

Deep Learning Applications for Cyber Sec

📁 Deep Learning Applications for Cyber Security

✍ Mamoun Alazab, MingJian Tang 📂 Library 📅 2019 🏛 Springer International Publishing 🌐 English

Cybercrime remains a growing challenge in terms of security and privacy practices. Working together, deep learning and cyber security experts have recently made significant advances in the fields of intrusion detection, malicious code analysis and forensic identification. This book addr

Deep Learning Approaches to Text Product

📁 Deep Learning Approaches to Text Production

✍ Shashi Narayan; Claire Gardent 📂 Library 📅 2020 🏛 Morgan & Claypool 🌐 English

Text production has many applications. It is used, for instance, to generate dialogue turns from dialogue moves, verbalise the content of knowledge bases, or generate English sentences from rich linguistic representations, such as dependency trees or abstract meaning representations. Text production