Overview

Adversarial machine learning poses a threat to cybersecurity by exploiting vulnerabilities in AI models through manipulated inputs. These attacks can cause systems in healthcare, finance, and autonomous vehicles to make dangerous or misleading decisions. A major challenge lies in detecting these small issues and defending learning models and organizational data without sacrificing performance. Ongoing research and cross-sector collaboration are essential to develop robust, ethical, and secure machine learning systems. Further research may reveal better solutions to converge cyber technology, security, and machine learning tools. Challenges and Solutions for Cybersecurity and Adversarial Machine Learning explores adversarial machine learning and deep learning within cybersecurity. It examines foundational knowledge, highlights vulnerabilities and threats, and proposes cutting-edge solutions to counteract adversarial attacks on AI systems. This book covers topics such as data privacy, federated learning, and threat detection, and is a useful resource for business owners, computer engineers, security professionals, academicians, researchers, and data scientists.

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9798337322018

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|Shafiq Ul Rehman - Editor|Dr. Shafiq Ul Rehman is an experienced educator and professional consultant with a background in curriculum development and educational technology. With over 10 years in the field, Dr. Shafiq has worked with various educational institutions to implement sustainable practices and innovative teaching strategies. Dr. Shafiq received his Ph.D. degree from Universiti Sains Malaysia (USM), Malaysia, in 2017. He was a Postdoctoral Research Fellow at Singapore University of Technology and Design (SUTD), Singapore, from 2017 to 2020. He is currently Acting Dean, College of Information Technology and Chairman Department of Computer Science, Kingdom University, Bahrain. He is also an Assistant Professor with research interests in cybersecurity, artificial intelligence, and the latest emerging IT technologies. He lectures in various Computer Science and IT courses, including developing curriculum and courseware in tandem with current technology trends. He has authored and coauthored more than 50 peer reviewed publications, published in journals, conference proceedings, and book chapters. He supervises Ph.D., postgraduate, and undergraduate students. He also gives talks and training on cybersecurity, artificial intelligence, and the latest emerging IT technologies at various organizations, conferences, seminars, and workshops.

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