The Art of Cyber Defense: From Risk Assessment to Threat Intelligence offers a comprehensive exploration of cybersecurity principles, strategies, and technologies essential for safeguarding digital assets and mitigating evolving cyber threats. This book provides invaluable insights into the intricacies of cyber defense, guiding readers through a journey from understanding risk assessment methodologies to leveraging threat intelligence for proactive defense measures.
Delving into the nuances of modern cyber threats, this 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.
This book offers comprehensive coverage of the most essential topics, including:
Advanced malware detection and prevention strategies leveraging artificial intelligence (AI)
Hybrid deep learning techniques for malware classification
Machine learning solutions and research perspectives on Internet of Services (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.
Reihe
Sprache
Verlagsort
Verlagsgruppe
Zielgruppe
Für Beruf und Forschung
Professional Practice & Development, Professional Reference, and Professional Training
Illustrationen
7 s/w Photographien bzw. Rasterbilder, 134 s/w Zeichnungen, 37 s/w Tabellen, 141 s/w Abbildungen
37 Tables, black and white; 134 Line drawings, black and white; 7 Halftones, black and white; 141 Illustrations, black and white
Maße
Höhe: 260 mm
Breite: 183 mm
Dicke: 21 mm
Gewicht
ISBN-13
978-1-032-71478-3 (9781032714783)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Klassifikation
Prof. Youssef Baddi is full-time Associate Professor at Chouaib Doukkali University UCD EL Jadida, Morocco. Phd Thesis degree in computer science from ENSIAS School, University Mohammed V Souissi of Rabat, Morocco, since 2016. He also holds a Research Master's degree in networking obtained in 2010 from the High National School for Computer Science and Systems Analysis - ENSIAS-Morocco-Rabat.
Prof. Mohammed Amin Almaiah obtained his PhD in Computer Science from University Malaysia Terengganu from Malaysia. MSc in Computer Information System from Middle East University (MEU) in 2011 from Jordan. He is now working as Associate Professor in the Department of Computer networks and Communications at King Faisal Saudi Arabia.
Prof. Omar Almomani received his bachelor's and master's degrees in telecommunication technology from the Institute of Information Technology at the University of Sindh in 2002 and 2003, respectively. In 2010, he received his Ph.D. in computer networking from the UUM. Currently, he is a professor at the Information Technology Faculty of the World Islamic Sciences and Education University.
Prof. Yassine Maleh is an Associate professor of cybersecurity and IT governance at Sultan Moulay Slimane University, Morocco, since 2019. He is the founding chair of IEEE Consultant Network Morocco and founding president of the African Research Center of Information Technology & Cybersecurity. He is a former CISO at the National Port Agency between 2012-2019. He is a senior member of IEEE and a member of the International Association of Engineers IAENG and The Machine Intelligence Research Labs.
Herausgeber*in
National School of Applied Sciences
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
