Machine Learning, Blockchain, and Cyber Security in Smart Environments (eBook, PDF)

Application and Challenges
Redaktion: Tanwar, Sarvesh; Rana, Ajay; Badotra, Sumit

• Format: PDF

Produktbeschreibung

Machine Learning, Cyber Security, and Blockchain in Smart Environment: Application and Challenges provides far-reaching insights into the recent techniques forming the backbone of smart environments, and addresses the vulnerabilities that give rise to the challenges in real-word implementation. The book focuses on the benefits related to the emerging applications such as machine learning, blockchain and cyber security.

Key Features:

• Introduces the latest trends in the fields of machine learning, blockchain and cyber security
• Discusses the fundamentals, challenges and architectural overviews with concepts
• Explores recent advancements in machine learning, blockchain, and cyber security
• Examines recent trends in emerging technologies

This book is primarily aimed at graduates, researchers, and professionals working in the areas of machine learning, blockchain, and cyber security.

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Produktdetails

• Verlag: Taylor & Francis eBooks
• Seitenzahl: 234
• Erscheinungstermin: 31. August 2022
• Englisch
• ISBN-13: 9781000623826
• Artikelnr.: 64438197

Autorenporträt

Sarvesh Tanwar, Sumit Badotra, Ajay Rana

Inhaltsangabe

1. Intelligent Green Internet of Things: An Investigation. 2. The Role of
Artificial Intelligence in the Education Sector: Possibilities and
Challenges. 3. Multidisciplinary Applications of Machine Learning. 4.
Prediction of Diabetes in the Early Stages using Machine-Learning Tools and
Microsoft Azure AI Services. 5. Advanced Agricultural Systems:
Identification, Crop Yields and Recommendation using Image Processing
Techniques and Machine-Learning Algorithms. 6. SP-IMLA: Stroke Prediction
using an Integrated Machine Learning Approach. 7. Multimodal Medical Image
Fusion using Laplacian Re-Decomposition. 8. Blockchain Technology-Enabled
Healthcare IoT to Increase Security and Privacy Using Fog Computing. 9.
Blockchain in Healthcare, Supply-Chain Management, and Government Policies.
10. Electricity and Hardware Resource Consumption in Cryptocurrency Mining.
11. Cryptographic Hash Functions and Attack Complexity Analysis. 12. Mixed
Deep Learning and Statistical Approach to Network Anomaly Detection. 13.
Intrusion Detection System Using Deep Learning Asymmetric Autoencoder