E-Book, Englisch, 397 Seiten, eBook
ISBN: 978-3-030-38557-6
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: Wasserzeichen (»Systemvoraussetzungen)
The second part of this handbook is focused on privacy and security issues in different layers of big data systems. It discusses about methods for evaluating security and privacy of big data systems on network, application and physical layers. This handbook elaborates on existing methods to use data analytic and AI techniques at different layers of big data platforms to identify privacy and security attacks. The final part of this handbook is focused on analyzing cyber threats applicable to the big data environments. It offers an in-depth review of attacks applicable to big data platforms in smart grids, smart farming, FinTech, and health sectors. Multiple solutions are presented to detect, prevent and analyze cyber-attacks and assess the impact of malicious payloads to those environments.
This handbook provides information for security and privacy experts in most areas of big data including; FinTech, Industry 4.0, Internet of Things, Smart Grids, Smart Farming and more. Experts working in big data, privacy, security, forensics, malware analysis, machine learning and data analysts will find this handbook useful as a reference. Researchers and advanced-level computer science students focused on computer systems, Internet of Things, Smart Grid, Smart Farming, Industry 4.0 and network analysts will also find this handbook useful as a reference.
Zielgruppe
Research
Autoren/Hrsg.
Weitere Infos & Material
1. Big Data and Privacy : Challenges and Opportunities.- 2. AI and Security of Critical Infrastructure.- 3. Industrial Big Data Analytics: Challenges and Opportunities.- 4. A Privacy Protection Key Agreement Protocol Based on ECC for Smart Grid.- 5. Applications of Big Data Analytics and Machine Learning in the Internet of Things.- 6. A Comparison of State-of-the-art Machine Learning Models for OpCode-Based IoT Malware Detection.- 7. Artificial Intelligence and Security of Industrial Control Systems.- 8. Enhancing Network Security via Machine Learning: Opportunities and Challenges.- 9. Network Security and Privacy Evaluation Scheme for Cyber Physical Systems (CPS).- 10. Anomaly Detection in Cyber-Physical Systems Using Machine Learning.- 11. Big Data Application for Security of Renewable Energy Resources.- 12. Big-Data and Cyber-Physical Systems in Healthcare: Challenges and Opportunities.- 13. Privacy Preserving Abnormality Detection: A Deep Learning Approach.-14. Privacy and Security in Smart and Precision Farming: A Bibliometric Analysis.- 15. A Survey on Application of Big Data in Fin Tech Banking Security and Privacy.- 16. A Hybrid Deep Generative Local Metric Learning Method For Intrusion Detection.- 17. Malware elimination impact on dynamic analysis: An experimental machine learning approach.- 18. RAT Hunter: Building Robust Models for Detecting Remote Access Trojans Based on Optimum Hybrid Features.- 19. Active Spectral Botnet Detection based on Eigenvalue Weighting.-