About the Book
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.
About the Author :
Ammar Almomani is an Internet Infrastructures Security and Cybersecurity based on AI specialist with a Ph.D. Degree in Computer Science from Universiti Sains Malaysia (USM), which is ranked #142 in the QS World University Rankings 2021. He is recognized as One of the Top 2% of Global Influential Researchers by Stanford University and the Scopus Index-Oct-2023. His academic background also includes a Master of Science in Computer Information Systems and a Bachelor of Computer Science. He has an extensive publication record, with over 113+ articles published in reputable journals and conferences, most of them in Scopus Q1 and Q2 categories, and 8 patents and utility models published as six German utility models and Two India-grated patents. More than 21 articles and patents are under revision. He has significant experience in 20 years of teaching more than 42 topics with various subjects related to cybersecurity and Cybersecurity Engineering area such as “Network Security, Wireless Computer Networks security, Cryptography, Cloud computing, and security special topics (Ethical hacking) Enterprises Information System Security, Big data analytics, artificial intelligence, cybersecurity, networks, communications, and programming languages. with many international certificates. He taught at reputable 5 academic institutions, Supervising many undergraduate and postgraduate students' research projects and theses (Masters/Ph.D.) from many countries such as the UK, Malaysia, Jordan ..etc. As a cybersecurity and Internet infrastructure security specialist, he actively contributed to the field by managing AI and cybersecurity projects with international teams of top researchers and universities. He has authored 76 Scopus articles, H-index-20, 1380 citations, and garnered over 2,762 citations on Google Scholar, with an H-index of 27. Also he actively engaged in the academic community, with a strong online presence and a large readership and following on ResearchGate with about 89390 readers and followers. Currently working at Faculty - Computer Information Science, Higher Colleges of Technology, Sharjah, UAE. He has Five years of management experience with a UAE Golden Visa Holder, and my focus is on improving educational institutes. Moreover, he has made significant contributions to the development of courses and programs, including ABET and AACSB Accreditation Dr. Mohammad Alauthman (contacted at email: mohammad.alauthman@uop.edu.jo) is an associate professor and chair of the Information Security Department at the Faculty of Information Technology, University of Petra inAmman, Jordan. His research interests lie in network security, intrusion detection systems,and the application of artificial intelligence techniques like machine learning and deep learning for botnet detection, DDoS detection, spam email filtering, IoT security, and network traffic classification. He obtained his Ph.D. in computer science with a focus on network security from Northumbria University in the UK in 2016. Alauthman has been awarded several research grants in the field of network security, supporting his work on advanced intrusion detection systems and the development of AI-driven security solutions. These grants have enabled him to conduct extensive research and collaborate with international experts. His funded projects have focused on enhancing the resilience of network infrastructures against emerging threats and improving the accuracy of threat detection mechanisms.
