Examining Cybersecurity Risks Produced by Generative AI

Examining Cybersecurity Risks Produced by Generative AI

Ammar Almomani (Higher Colleges of Technology, UAE) and Mohammad Alauthman (University of Petra, Jordan)
Release Date: May, 2025|Copyright: © 2025 |Pages: 702
DOI: 10.4018/979-8-3373-0832-6
ISBN13: 9798337308326|ISBN13 Softcover: 9798337308333|EISBN13: 9798337308340
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Description & Coverage
Description:

As generative artificial intelligence (AI) evolves, it introduces new opportunities across industries, from content creation to problem-solving. However, with these advancements come significant cybersecurity risks that demand closer scrutiny. Generative AI, capable of producing text, images, code, and deepfakes, presents challenges in cybersecurity. Malicious scammers could leverage these technologies to automate cyberattacks, create sophisticated phishing schemes, or bypass traditional security systems with efficiency. This intersection of cutting-edge AI and cybersecurity concerns requires new organizational safeguards for digital environments, highlighting the need for new protocols, regulations, and proactive defense mechanisms to mitigate potential threats.

Examining Cybersecurity Risks Produced by Generative AI addresses the intersections of generative AI with cybersecurity, presenting its applications, potential risks, and security frameworks designed to harness its benefits while mitigating challenges. It provides a comprehensive, up-to-date resource on integrating generative models into cybersecurity practice and research. This book covers topics such as deepfakes, smart cities, and phishing attacks, and is a useful resource for computer engineers, security professionals, business owners, policymakers, academicians, researchers, and data scientists.

Coverage:

The many academic areas covered in this publication include, but are not limited to:

  • Cybersecurity
  • Deepfakes
  • Ethics and Law
  • Generative Artificial Intelligence
  • Human-Computer Interaction (HCI)
  • Impersonation Attacks
  • Malware and Ransomware
  • Metaverse
  • Phishing Attacks
  • Quantum Computing
  • Risk Management
  • Smart Cities
  • Social Engineering
  • Supply Chains
  • Threat Detection
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Editor/Author Biographies
Ammar Almomani earned his Ph.D. in Advanced Internet Security and Monitoring from Universiti Sains Malaysia (2013). He is a Professor at the Higher Colleges of Technology, UAE, and a consultant in AI and cybersecurity. Dr. Almomani has over 20 years of experience in academia and industry, specializing in areas such as network security, cryptography, and IoT-based cybersecurity. Recognized among the top 2% of researchers worldwide, he has authored over 150 publications and holds several patents. He has also played key roles in curriculum development and accreditation processes for academic programs​.
Mohammad Alauthman is an Associate Professor in the Information Security Department at the Faculty of Information Technology, University of Petra, Amman, Jordan. His research interests include network security, intrusion detection systems, and applying AI techniques—such as machine learning and deep learning—for botnet and DDoS detection, spam filtering, IoT security, and network traffic classification. He earned his Ph.D. in Computer Science from Northumbria University, UK, in 2016. Dr. Alauthman has received multiple research grants supporting advanced AI-driven intrusion detection systems and international collaboration. He is also actively involved in Erasmus+ projects, including BITTCOIN-JO (technology transfer), RL4Eng (remote engineering labs), Pro-GREEN LABs (green competences in education), and COMMO (mobility and cooperation across Mediterranean and Balkan institutions), contributing to innovation, sustainability, and cross-border academic development.
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