Buch, Englisch, 304 Seiten, Format (B × H): 178 mm x 254 mm
From Risk Assessment to Threat Intelligence
Buch, Englisch, 304 Seiten, Format (B × H): 178 mm x 254 mm
ISBN: 978-1-03-271478-3
Verlag: Taylor & Francis Ltd
Delving into the nuances of modern cyber threats, the book equips readers with the knowledge and tools necessary to navigate the complex landscape of cybersecurity. Through a multidisciplinary approach, it addresses the pressing challenges organizations face in securing their digital infrastructure and sensitive data from cyber-attacks.
The book offers comprehensive coverage of the most essential topics, including:
- Advanced malware detection and prevention strategies leveraging AI.
- Hybrid deep learning techniques for malware classification.
- Machine learning solutions and research perspectives on IoT security.
- Comprehensive analysis of blockchain techniques for enhancing IoT security and privacy.
- Practical approaches to integrating security analysis modules for proactive threat intelligence.
This book is an essential reference for students, researchers, cybersecurity professionals, and anyone interested in understanding and addressing contemporary cyber defense and risk assessment challenges. It provides a valuable resource for enhancing cybersecurity awareness, knowledge, and practical skills.
Zielgruppe
Professional Practice & Development, Professional Reference, and Professional Training
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik EDV | Informatik Computerkommunikation & -vernetzung Netzwerksicherheit
- Mathematik | Informatik EDV | Informatik Technische Informatik Computersicherheit Datensicherheit, Datenschutz
- Mathematik | Informatik EDV | Informatik Technische Informatik Computersicherheit Schadprogramme (Viren, Trojaner etc.)
- Mathematik | Informatik EDV | Informatik Technische Informatik Computersicherheit Kryptographie, Datenverschlüsselung
Weitere Infos & Material
Part I: Foundations of Cyber Defense and Risk Assessment
Chapter 1: AI-Powered Strategies for Advanced Malware Detection and Prevention
Chapter 2: Advancing Malware Classification with Hybrid Deep Learning
Chapter 3: A Comprehensive Overview of AI-Driven Behavioral Analysis for Security in Internet of Things
Chapter 4: A Deep Dive into IoT Security: Machine Learning Solutions and Research Perspectives
Chapter 5: Exploring Blockchain Techniques for Enhancing IoT Security and Privacy: A Comprehensive Analysis
Part II: Analyzing and Responding to Emerging Threats
Chapter 6: Integrating Security Analysis Module for Proactive Threat Intelligence
Chapter 7: Security Study of Web Applications through a White Box Audit Approach: A Case Study
Chapter 8: Case Study Method: A Step-by-Step Black Box Audit for Security Study of Web Applications
Chapter 9: Security in Cloud-Based IoT: A Survey
Chapter 10: Exploring IoT penetration testing: From fundamentals to practical setup
Chapter 11: A Fuzzy Logic-Based trust system for detecting selfish nodes and encouraging cooperation in Optimized Link State Routing protocol
Chapter 12: Collaborative Cloud-SDN Architecture for IoT Privacy-Preserving Based on Federated Learning
Chapter 13: An adaptive cybersecurity strategy based on game theory to manage emerging threats In The SDN Infrastructure
Part III: Human-Centric Risk Mitigation Approaches
Chapter 14: A Human-Centric Approach to Cyber Risk Mitigation
Chapter 15: Human Factors in Cyber Defense
Chapter 16: Security Operation Center: Towards A Maturity Model