AI and ML-Driven Cybersecurity

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A01=Atdhe Buja
anomaly detection
artificial intelligence
Author_Atdhe Buja
Category=JKVC
Category=URH
Category=UT
Category=UYF
Category=UYQ
cybersecurity
data-driven security
edge computing
eq_bestseller
eq_computing
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
eq_society-politics
federated learning
industrial control systems
machine learning
predictive analytics
threat detection in sensor networks

Product details

  • ISBN 9781041050391
  • Weight: 420g
  • Dimensions: 156 x 234mm
  • Publication Date: 17 Nov 2025
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Hardback
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While the Industrial Internet of Things (IIoT) and Wireless Sensor Networks (WSNs) continue to redefine industrial infrastructure, the need for proactive, intelligent, and scalable cybersecurity solutions has never been more pressing. This book provides a hands-on, research-driven guide to building, deploying, and understanding machine learning models tailored for securing IIoT and WSN environments.

Whether you’re a student, researcher, or professional, this book takes you through the full data science lifecycle—from data collection and EDA to model development and deployment—with a special focus on real-world attack detection, anomaly analysis, and predictive defense strategies.

You’ll learn:

  • How to run a cybersecurity-focused exploratory data analysis (EDA)
  • Step-by-step model design, training, and evaluation for threat detection
  • Building and deploying web-based AI cybersecurity solutions
  • Practical use of Python
  • Visualizing attacks and insights to drive decision-making
  • Future trends including Edge AI, federated learning, and zero-trust security

This book is intended for cybersecurity professionals working in industrial or smart environments, including smart cities, aerospace, manufacturing, etc. It is also a valuable resource for data scientists and ML engineers applying AI to security, industrial engineers, and university students and educators in computer science, data science, and security. Build secure, data-driven defenses for the next generation of connected systems—start here.

Atdhe Buja, Commonwealth University of Pennsylvania, Bloomsburg. Atdhe Buja is an assistant Professor in the Department of Computer Science, Math, and Digital Forensics at the Commonwealth University of Pennsylvania, Bloomsburg. He is a world-renowned cybersecurity expert with decades of experience and a leader in information technology and Industrial IoT cybersecurity. His work has been presented at several conferences, including FIRST cybersecurity, Hackathons, Astana IT University, Balkan Cybersecurity DCAF, Japan, cybersecurity Workshops, Safer Internet Day, etc. Participated many times in DEFCON, is a well-known expert on CERT teams where he developed and built CERT in academia and private (ICT Academy CERT), and has held a variety of roles in the cybersecurity industry. He has developed several video courses for the industry and the ICT Academy on VAPT, Incident Handling, SOC, Pentest, Machine Learning Introduction, IoT Security, Attack Scenarios and Incident Response, and cyber systems and Network Forensics. Leading many research projects for ICT Academy with Astana International Scientific Complex and Global Cyber Alliance, developing innovative solutions leveraging Machine Learning, Artificial Intelligence, and Cybersecurity to meet the needs of Wireless Sensor Networks, the Internet of Things, and Industrial IoT.

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