Ai-driven Security Systems and Intelligent Threat Response Using Autonomous Cyber Defense

AI-driven security systems and intelligent threat response using autonomous cyber defense represent the cutting edge of cybersecurity technology. As cyber threats become more sophisticated, traditional defense mechanisms struggle to keep up with the scale and speed of attacks. AI-powered security systems utilize machine learning, pattern recognition, and data analysis to detect vulnerabilities, predict breaches, and respond to threats. These systems can learn from emerging threats, adapting to new attack methods and autonomously executing countermeasures without human intervention. By using advanced algorithms to recognize anomalies and mitigate risks, autonomous cyber defense offers a proactive solution to protect sensitive data and networks, ensuring faster responses to cyber incidents. AI-Driven Security Systems and Intelligent Threat Response Using Autonomous Cyber Defense delves into the cutting-edge integration of autonomous systems in cybersecurity, emphasizing AI-driven threat detection, response, and system resilience. It bridges the gap between traditional cybersecurity methods and emerging autonomous defense systems, presenting in-depth coverage of AI-driven security mechanisms, automated threat responses, and intelligent defense strategies. This book covers topics such as cybersecurity, infrastructure, and defense systems, and is a useful resource for engineers, security professionals, business owners, academicians, researchers, and computer scientists.

Dr. Mohammad Alauthman (mohammad.alauthman@uop.edu.jo) 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.

Professor Ammar Ali Almomani He is a Cybersecurity Based on AI, specialist with a Ph.D. Degree in advanced internet security and monitoring from Universiti Sains Malaysia (USM), 20 Years of Teaching and industrial experience, exposure to innovation and entrepreneurship. 6 years of management included around 3 years as Head of the Research and Innovation Department, - One of the Top 2% of Global Influential Researchers by Stanford University and the Scopus Index-2023-2024. - Consultant and Expert member in UAE Research Map (R&D) - I have an extensive publication record, with over 150 + articles published in reputable journals and conferences, most of them in Scopus Q1 and Q2 categories, 100 Scopus articles, Scopus citations=1950, H-index=22, and 10 patents published as Eight Germany and Two India granted patents. 4100 Citations on Google Scholar, with an H-index of 31. I-index= 68. - More than 20 articles, books, and conferences are under revision in 2024. worked in AL-Balqa Applied University -Jordan and Currently, working in the Computer Information Science (CIS) program, Bachelor of Cybersecurity, at Higher Colleges of Technology (HCT), Sharjah, UAE.