IoT Cybersecurity : Trends, Challenges, and Solutions (Advances in Computational Collective Intelligence)

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IoT Cybersecurity : Trends, Challenges, and Solutions (Advances in Computational Collective Intelligence)

  • ウェブストア価格 ¥43,084(本体¥39,168)
  • Auerbach(2026/05発売)
  • 外貨定価 US$ 200.00
  • 読書週間 ポイント2倍キャンペーン 対象商品(~11/9)
  • ポイント 782pt
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  • 製本 Hardcover:ハードカバー版/ページ数 248 p.
  • 言語 ENG
  • 商品コード 9781032958781

Full Description

IoT systems create a massive attack surface with billions of connected devices that often have weak default credentials and limited security capabilities, making them easy targets for cybercriminals to exploit at scale. Compromised IoT devices can serve as entry points for attackers to access valuable network resources, steal sensitive personal and business data, or launch large-scale botnet attacks that disrupt critical infrastructure. Without proper security measures, IoT vulnerabilities can lead to serious consequences including operational disruptions, safety hazards in critical systems like healthcare and transportation, and significant financial and legal penalties from regulatory non-compliance. IoT Cybersecurity: Trends, Challenges, and Solutions addresses the significant knowledge gap between rapidly deployed connected devices and understanding their unique security challenges. Highlights include:

An efficient lightweight cryptography technique for enhancing IoT security
Machine learning approaches for IoT network threat detection and security optimization
Using AI to enhance IoT-based intrusion detection systems
A study on emerging threats and vulnerabilities

The book presents research and insights into practice that explore security holes and effective solutions in the realm of IoT cybersecurity. Covering the evolving threat landscape in IoT environments, it sheds light on the intricacies of cybersecurity patterns and addresses the challenges that arise. The book is a resource offering innovative solutions, research findings, case studies, and practical insights related to securing IoT ecosystems.

Contents

1. An Efficient Lightweight Cryptography Technique for Enhancing IoT Security 2. Enhancement of IoT-Based Intrusion Detection Systems by AI and ML Methodologies 3. Hardware Trojan Vulnerability in IoT End Devices: A Walkthrough 4. Securing the Internet of Things: Proactive Firewalls and the Challenges of Big Data 5. The Human Firewall: Strengthening IoT Security Through Behavior 6. Enhancing IoT Security with Cryptographic Approach 7. Cybersecurity Challenges on the Internet of Things: A Study on Emerging Threats and Vulnerabilities 8. Synergizing Machine Learning and Artificial Intelligence in Internet of Things Environments: Transformative Applications and Future Direction 9. Intelligent Machine Learning Approaches for IoT Network Threat Detection and Security Optimization 10. A Comprehensive Review of AI and IoT-Based Systems for Intelligent Accident Management and Response 11. Navigating the Future of IoT Security: Emerging Trends, Challenges and Strategic Solutions

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