Cyber Security and Business Intelligence - Innovations and Machine Learning for Cyber Risk Management


To cope with the competitive worldwide marketplace, organizations rely on business intelligence to an increasing extent. Cyber security is an inevitable practice to protect the entire business sector and its customer. This book presents the significance and application of cyber security for safeguarding organizations, individuals’ personal information and government. The book provides both practical and managerial implications of cyber security that also supports business intelligence and discusses the latest innovations in cyber security. It offers a roadmap to master’s degree students and Ph.D. researchers for cyber security analysis in order to minimize the cyber security risk and protect customers from cyber-attack. The book also introduces the most advanced and novel machine learning techniques including, but not limited to, Support Vector Machine, Neural Networks, Extreme Learning Machine, Ensemble Learning, and Deep Learning Approaches, with a goal to apply those on cyber risk management datasets. It will also leverage real-world financial instances to practice business product modelling and data analysis. The contents of this book will be useful for a wide audience who are involved in managing network systems, data security, data forecasting, cyber risk modelling, fraudulent credit risk detection, portfolio management, and data regulatory bodies. It will be particularly beneficial to academics as well as practitioners who are looking to protect their IT system, reduce data breaches and cyber-attack vulnerabilities.

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Product Description

To cope with the competitive worldwide marketplace, organizations rely on business intelligence to an increasing extent. Cyber security is an inevitable practice to protect the entire business sector and its customer. This book presents the significance and application of cyber security for safeguarding organizations, individuals’ personal information and government. The book provides both practical and managerial implications of cyber security that also supports business intelligence and discusses the latest innovations in cyber security. It offers a roadmap to master’s degree students and Ph.D. researchers for cyber security analysis in order to minimize the cyber security risk and protect customers from cyber-attack. The book also introduces the most advanced and novel machine learning techniques including, but not limited to, Support Vector Machine, Neural Networks, Extreme Learning Machine, Ensemble Learning, and Deep Learning Approaches, with a goal to apply those on cyber risk management datasets. It will also leverage real-world financial instances to practice business product modelling and data analysis. The contents of this book will be useful for a wide audience who are involved in managing network systems, data security, data forecasting, cyber risk modelling, fraudulent credit risk detection, portfolio management, and data regulatory bodies. It will be particularly beneficial to academics as well as practitioners who are looking to protect their IT system, reduce data breaches and cyber-attack vulnerabilities.

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Product Details

General

Imprint

Taylor & Francis

Country of origin

United Kingdom

Series

Routledge Studies in Innovation, Organizations and Technology

Release date

December 2023

Availability

Expected to ship within 9 - 15 working days

First published

2024

Editors

,

Dimensions

234 x 156mm (L x W)

Pages

256

ISBN-13

978-1-03-225957-4

Barcode

9781032259574

Categories

LSN

1-03-225957-4



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