- ホーム
- > 洋書
- > 英文書
- > Computer / General
Full Description
A practical guide to designing secure and energy-efficient IoT networks through cross-layer frameworks, lightweight cryptography, and machine learning-based intrusion detection, Improving Security and Energy Efficiency in IoT Networks equips readers with actionable strategies to balance security and energy efficiency in resource-constrained IoT environments. It delivers hands-on frameworks validated through simulations and hardware testbeds, covering adaptive routing, lightweight encryption, and ML-driven anomaly detection. It also includes mini-projects, review questions, and reproducible configurations for real-world deployments.
Key Features:
Effectively balances security and energy efficiency through cross-layer design principles.
Comprehensively integrates lightweight cryptography, adaptive routing, and ML-based anomaly detection.
Practically validates concepts with simulations, hardware testbeds, and hands-on mini projects.
Companion resources include configuration files, scripts, and experiment notes to support reproducibility and classroom use.
Ideal for IoT practitioners, network engineers, cybersecurity professionals, and researchers seeking practical solutions for secure and sustainable IoT systems. Also suited for instructors and students in networking, embedded systems, and cybersecurity courses.
Contents
Chapter 1: Introduction includes subtopics 1.1 Opening Insights, 1.2 Knowledge Outcomes, 1.3 Research Methodology for Investigation, 1.4 Contributions and the Structure of This Book, 1.5 Summary, 1.6 Key Terms, 1.7 Review Questions, and 1.8 Mini Projects. Chapter 2: Internet of Things Cross-Layer Approaches covers 2.1 Introduction, 2.2 Secure and Energy-Efficient Layered IoT Networks, 2.3 A Review of Literature on Cross-Layer IoT Networks, 2.4 Cross-Layer IoT Framework, 2.5 Energy Effectiveness and Security Measures of IoT Networks, 2.6 Autonomous Cross-Layer Framework for IoT Network, 2.7 Research Issues, 2.8 Enhancing Cross-Layer IoT Security and Efficiency Design, 2.9 Summary, 2.10 Key Terms, 2.11 Review Questions, and 2.12 Mini Projects. Chapter 3: Internet of Things Layered Architecture includes 3.1 Introduction, 3.2 Integration of Emerging Technologies in Cross-Layer Frameworks, 3.3 Methodological Approaches for Cross-Layer Optimization, 3.4 Cross-Layer Solutions in Smart Cities and Healthcare, 3.5 Performance Metrics and Evaluation Techniques, 3.6 IoT Layered Architecture, 3.7 Quality Standards and Trustworthiness, 3.8 Industrial Internet of Things (IIoT), 3.9 MAC-Routing, 3.10 Energy-Efficient Cross-Layer Design, 3.11 Key Strategies and Trends, 3.12 Summary, 3.13 Key Terms, 3.14 Review Questions, and 3.15 Mini Projects. Chapter 4: Research Design and Methodology includes 4.1 Learning Objectives, 4.2 Introduction, 4.3 Cross-Layer Architecture Design, 4.4 Simulation Environment and Tools, 4.5 Performance Evaluation Metrics, 4.6 Machine Learning Integration, 4.7 Comparative Analysis and Validation, 4.8 Mathematical Models and Proofs, 4.9 Summary, 4.10 Key Terms, 4.11 Review Questions, and 4.12 Mini Projects. Chapter 5: Proposed Cross-Layer Framework includes 5.1 Introduction, 5.2 Energy-Aware IoT Security Frameworks, 5.3 Cross-Layer Data Flow and Routing Protocols for IoT Efficiency, 5.4 Proposed Cross-Layer Framework, 5.5 Results and Discussion, 5.6 Summary, 5.7 Key Terms, 5.8 Review Questions, and 5.9 Mini Project. Chapter 6: Lightweight Cross-Layer Framework Encryption includes 6.1 Introduction, 6.2 Secure and Energy-Efficient Cross-Layer Framework Advancements, 6.3 Addressing IoT Security and Energy Efficiency, 6.4 Core Contributions and Framework Validation, 6.5 IoT Security and Energy Optimization Trends, 6.6 Proposed Secure and Energy-Efficient Architecture, 6.7 Performance Evaluation and Simulation Setup, 6.8 Results and Discussion, 6.9 Result Validation, 6.10 Summary, 6.11 Key Terms, 6.12 Review Questions, and 6.13 Mini Project. Chapter 7: Cross-Layer Framework Machine Learning Models includes 7.1 Introduction, 7.2 Security-Energy Trade-Offs, 7.3 Machine Learning-Enhanced Validation of Lightweight IoT Protocols, 7.4 IoT Gaps and ML Anomaly Detection, 7.5 Performance Evaluation and Proposed Architecture, 7.6 Development Environment and Experiment Setup, 7.7 Analysis of Energy-Efficient and Secure IoT Architecture, 7.8 Analysis Machine Learning Cross-Layer Framework, 7.9 Summary, 7.10 Key Terms, 7.11 Review Questions, and 7.12 Mini Projects. Chapter 8: Design and Validation of IoT Deployment Architectures includes 8.1 Introduction, 8.2 An Evolutionary Path for Adopting IoT, 8.3 Deployment of IoT Scenarios, 8.4 Real-World Case Studies and Hardware-Based Security Considerations, 8.5 Single-Floor Office Scenario, 8.6 Multi-Floor Office Scenario, 8.7 Summary of Findings, 8.8 Summary, 8.9 Key Terms, 8.10 Review Questions, and 8.11 Mini Projects. Chapter 9: Breakthroughs in Internet of Thing Technologies includes 9.1 Introduction, 9.2 Recent Developments in IoT, 9.3 Emerging Data Challenges in Modern IoT Systems, 9.4 Summary, 9.5 Key Terms, 9.6 Review Questions, 9.7 Mini Projects, and References.
