Cyber Security and Business Intelligence
Innovations and Machine Learning for Cyber Risk Management
- 222 pages
- English
- ePUB (mobile friendly)
- Available on iOS & Android
Cyber Security and Business Intelligence
Innovations and Machine Learning for Cyber Risk Management
About this book
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 degree students and PhD 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 to cyber risk management datasets. It will also leverage real-world financial instances to practise 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, and reduce data breaches and cyber-attack vulnerabilities.
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Information
Table of contents
- Cover
- Half Title
- Series Page
- Title Page
- Copyright Page
- Table of Contents
- List of contributors
- 1 Leveraging Business Intelligence to Enhance Cyber Security Innovation
- 2 Cyber Risk and the Cost of Unpreparedness of Financial Institutions
- 3 Cyber Security in Banking Sector
- 4 Is the Application of Blockchain Technology in Accounting Feasible? A Developing Nation Perspective
- 5 Empirical Analysis of Regression Techniques to Predict the Cybersecurity Salary
- 6 Test Plan for Immersive Technology-Based Medical Support System
- 7 Current Challenges of Hand-Based Biometric Systems
- 8 Investigating Machine Learning Algorithms with Model Explainability for Network Intrusion Detection
- 9 How Much Do the Features Affect the Classifiers on UNSW-NB15? An XAI Equipped Model Interpretability
- 10 On the Selection of Suitable Dimensionality Reduction and Data Balancing Techniques to Classify DarkNet Access on CICDarknet2020
- 11 An Effective Three-Layer Network Security to Prevent Distributed Denial of Service (DDoS) Attacks in Early Stages
- 12 Information Hiding Through a Novel DNA Steganography Technique to Secure Text Communication
- 13 An Explainable AI-Driven Machine Learning Framework for Cybersecurity Anomaly Detection
- Index