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Frontiers of Quality Electronic Design (QED) [electronic resource] : AI, IoT and Hardware Security /

Contributor(s): Material type: TextTextPublisher: Cham : Springer International Publishing : Imprint: Springer, 2023Edition: 1st ed. 2023Description: XX, 679 p. 372 illus., 275 illus. in color. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783031163449
Subject(s): Additional physical formats: Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleDDC classification:
  • 621.3815 23
LOC classification:
  • TK7867-7867.5
Online resources:
Contents:
Chapter 1. NAND Flash Memory Devices Security Enhancement Based on Physical Unclonable Functions -- Chapter 2. ReRAM based Neuromorphic Computing -- Chapter 3. Flash Technology for VLSI Design -- Chapter 4. Non-volatile memory Technologies:Characteristics,Deployment and Research Challenges -- Chapter 5. Data Analytics and Machine Learning for Coverage Closure -- Chapter 6. Cell-Aware Model Generation by Using Machine Learning -- Chapter 7. Neuromorphic Computing: A Path to Artificial Intelligence through Emulating Human Brains -- Chapter 8. AI for Cybersecurity in Distributed Automotive IoT Systems -- Chapter 9. Ultra-low Power Implementation of Neural Networks Using Inverter-based Memristive Crossbars -- Chapter 10. AI based Hardware Security Methods for Internet-of-Things Applications -- Chapter 11. Enabling Edge Computing Using Emerging Memory Technologies: From Device to Architecture -- Chapter 12. IoT Commercial, Industrial Applications and AI-powered IoT -- Chapter 13. Hardware and SystemSecurity - Attacks and Coun- termeasures Against Hardware Trojans -- Chapter 14. FPGA Security: Security Threats from Untrusted FPGA CAD Toolchain -- Chapter 15. DoS Attack Models and Mitigation Frameworks for NoC-based SoCs -- Chapter 16. Defense against security threats with regard to SoC Life Cycle -- Chapter 17. Defect Diagnosis Techniques for Silicon Customer Returns.
In: Springer Nature eBookSummary: Quality Electronic Design (QED)’s landscape spans a vast region where territories of many participating disciplines and technologies overlap. This book explores the latest trends in several key topics related to quality electronic design, with emphasis on Hardware Security, Cybersecurity, Machine Learning, and application of Artificial Intelligence (AI). The book includes topics in nonvolatile memories (NVM), Internet of Things (IoT), FPGA, and Neural Networks. Discusses state-of-the-art in electronics design process, semiconductor memories, FPGA, hardware security, and cybersecurity; Highlights trends, challenges and solutions; Explores application of Machine Learning and Artificial Intelligence in design.
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Chapter 1. NAND Flash Memory Devices Security Enhancement Based on Physical Unclonable Functions -- Chapter 2. ReRAM based Neuromorphic Computing -- Chapter 3. Flash Technology for VLSI Design -- Chapter 4. Non-volatile memory Technologies:Characteristics,Deployment and Research Challenges -- Chapter 5. Data Analytics and Machine Learning for Coverage Closure -- Chapter 6. Cell-Aware Model Generation by Using Machine Learning -- Chapter 7. Neuromorphic Computing: A Path to Artificial Intelligence through Emulating Human Brains -- Chapter 8. AI for Cybersecurity in Distributed Automotive IoT Systems -- Chapter 9. Ultra-low Power Implementation of Neural Networks Using Inverter-based Memristive Crossbars -- Chapter 10. AI based Hardware Security Methods for Internet-of-Things Applications -- Chapter 11. Enabling Edge Computing Using Emerging Memory Technologies: From Device to Architecture -- Chapter 12. IoT Commercial, Industrial Applications and AI-powered IoT -- Chapter 13. Hardware and SystemSecurity - Attacks and Coun- termeasures Against Hardware Trojans -- Chapter 14. FPGA Security: Security Threats from Untrusted FPGA CAD Toolchain -- Chapter 15. DoS Attack Models and Mitigation Frameworks for NoC-based SoCs -- Chapter 16. Defense against security threats with regard to SoC Life Cycle -- Chapter 17. Defect Diagnosis Techniques for Silicon Customer Returns.

Quality Electronic Design (QED)’s landscape spans a vast region where territories of many participating disciplines and technologies overlap. This book explores the latest trends in several key topics related to quality electronic design, with emphasis on Hardware Security, Cybersecurity, Machine Learning, and application of Artificial Intelligence (AI). The book includes topics in nonvolatile memories (NVM), Internet of Things (IoT), FPGA, and Neural Networks. Discusses state-of-the-art in electronics design process, semiconductor memories, FPGA, hardware security, and cybersecurity; Highlights trends, challenges and solutions; Explores application of Machine Learning and Artificial Intelligence in design.

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