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Full Description
In the digital finance world, cybersecurity and cloud tools can be used to prevent attacks and secure sensitive information such as the data of business transactions, internal payments, interbank payments, bank accounts, loan and deposit accounts, stocks, and other finance transactions.
The book explores the importance of artificial intelligence (AI)--based predictive cybersecurity tools in the financial industry and their role in protecting financial data. As AI continues to revolutionize the landscape of global transactions, it also brings forth new challenges, including sophisticated theft activities. Therefore, this book shares the problem of enhancing security and attack prevention through the application of AI-powered cybersecurity tools.
This book contributes to a deeper understanding of the importance of virus detection tools, unauthorized access detection tools, cloud services, and real-time predictive analytics in the finance industry as well as their pivotal role in cybersecurity for preventing data theft. The book provides valuable insights for the cybersecurity and cloud services in the financial services industry, that administrators, engineers, and managers to fortify the security and resilience of financial data systems in the face of evolving challenges of financial data theft.
This book is not merely a compilation of technical knowledge -- through its engaging and thought-provoking contents, the book leaves an indelible impression, urging readers to embrace the transformative power of AI-based technologies and embark on a collective mission to unlock the full potential of Cybersecurity as well as Cloud services for the betterment safety of global financial ecosystem.
Contents
Chapter 1. Role of Artificial Intelligence and Cybersecurity in Banking Industry Chapter 2. AI-Based Blockchain Technology for Security in Financial Sector Chapter 3. The Evolution of Cybersecurity Technologies in Banking and Finance Chapter 4. Navigating Cyber Threats: The Integration of AI in Banking Security Frameworks Chapter 5. Application of Blockchain-Driven Data Security in Smart Environments Chapter 6. Blockchain Technology and AI's Significance for Cyber Security in the Digital Economy Chapter 7. Cyber-Physical Systems Integration Issues and Data Processing Platform in the IoT Framework Chapter 8. Internet of Things (IoT) Data Visualizations for Business Insight in Finance Industry Chapter 9. Machine Learning-based Security Orchestration, Automation, and Response (SOAR) for Financial Institutions Chapter 10. Financial Forecasting and Cybersecurity with Convolutional Neural Networks: Trends and Challenges Chapter 11. AI Cybersecurity in Banking: Meeting Global Rules beyond EU AI ACT with Trusted Service Chapter 12. The Role of AI and Fintech in Strengthening Transnational Anti-Money Laundering Compliance Chapter 13. Quantum Cybersecurity Technologies in Banking and Finance Chapter 14. Anomaly Detection Driven by Machine Learning: Enhancing SIEM Tools for Sturdy Cyber Defense Chapter 15. Artificial Intelligence (AI)-Powered Innovation in Mortgage Banking Chapter 16. Application of Unified Payment Interface in Transforming the Digital Landscape of National Banking Chapter 17. Generative AI: A Review of Continuous Evolving Information Generation Perspective Chapter 18. Application of Artificial Intelligence in Cybersecurity Chapter 19. Security Risks at the Software-Defined Networking Architecture and Infrastructure Layer Chapter 20. Federated Blockchain based System for Managing Client Complaints Chapter 21. Big Data Analytics for Fraud Detection in Financial Transactions Chapter 22. Cloud and Cybersecurity for Banking and Finance Services Chapter 23. Data Privacy Challenges and Innovations in the Metaverse Financial Ecosystem Chapter 24. Opportunities, Issues, and Challenges of AI in Cybersecurity
