| Description |
1 online resource : illustrations. |
| Bibliography |
Includes bibliographical references and index. |
| Contents |
Machine learning attack models / Jing Lin, Long Dang, Mohamed Rahouti, Kaiqi Xiong -- Adversarial machine learning : a new threat paradigm for next-generation wireless communications / Yalin E. Sagduyu, Yi Shi, Tugba Erpek, William Headley, Bryse Flowers, George Stantchev, Zhuo Lu, and Brian Jalaian -- Threat of adversarial attacks to deep learning : a survey / Linsheng He, Fei Hu. |
| Summary |
"Today Artificial Intelligence (AI) and Machine/Deep Learning (ML/DL) have become the hottest areas in the information technology. In our society, there are so many intelligent devices that rely on AI/ML/DL algorithms/tools for smart operations. Although AI/ML/DL algorithms/tools have used in many Internet applications and electronic devices, they are also vulnerable to various attacks and threats. The AI parameters may be distorted by the internal attacker; the DL input samples may be polluted by adversaries; the ML model may be misled by changing the classification boundary, and many other attacks/threats. Those attacks make the AI products dangerous to use. While the above discussion focuses on the security issues in AI/ML/DL-based systems (i.e., securing the intelligent systems themselves), AI/ML/DL models/algorithms can be used for cyber security (i.e., use AI to achieve security). Since the AI/ML/DL security is a new emergent field, many researchers and industry people cannot obtain detailed, comprehensive understanding of this area. This book aims to provide a complete picture on the challenges and solutions to the security issues in various applications. It explains how different attacks can occur in advanced AI tools and the challenges of overcoming those attacks. Then many sets of promising solutions are described to achieve AI security and privacy in this book. The features of this book consist of 7 aspects: This is the first book to explain various practical attacks and countermeasures to AI systems; Both quantitative math models and practical security implementations are provided; It covers both "securing the AI system itself" and "use AI to achieve security"; It covers all the advanced AI attacks and threats with detailed attack models; It provides the multiple solution spaces to the security and privacy issues in AI tools; The differences among ML and DL security/privacy issues are explained. Many practical security applications are covered"-- Provided by publisher. |
| Biography |
Dr. Fei Hu is a professor in the department of Electrical and Computer Engineering at the University of Alabama. He has published over 10 technical books with CRC press. His research focus includes cyber security and networking. He obtained his Ph.D. degrees at Tongji University (Shanghai, China) in the field of Signal Processing (in 1999), and at Clarkson University (New York, USA) in Electrical and Computer Engineering (in 2002). He has published over 200 journal/conference papers and books. Dr. Hu's research has been supported by U.S. National Science Foundation, Cisco, Sprint, and other sources. He won the school's President's Faculty Research Award (<1% faculty were awarded each year) in 2020. Dr. Xiali (Sharon) Hei is an assistant professor in the School of Computing and Informatics at the University of Louisiana at Lafayette. Her research focus is cyber and physical security. Prior to joining the University of Louisiana at Lafayette, she was an assistant professor at Delaware State University from 2015-2017 and Frostburg State University 2014-2015. Sharon received his Ph.D. in computer science from Temple University in 2014, focusing on computer security. |
| Subject |
Computer networks -- Security measures.
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Machine learning -- Security measures.
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Deep learning (Machine learning) -- Security measures.
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Computer security -- Data processing.
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Artificial intelligence.
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Réseaux d'ordinateurs -- Sécurité -- Mesures. |
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Apprentissage automatique -- Sécurité -- Mesures. |
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Apprentissage profond -- Sécurité -- Mesures. |
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Sécurité informatique -- Informatique. |
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Intelligence artificielle. |
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artificial intelligence. |
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Artificial intelligence |
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Computer networks -- Security measures |
| Added Author |
Hu, Fei, 1972- editor.
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Hei, Xiali, editor.
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| Other Form: |
Print version: AI, machine learning and deep learning First edition. Boca Raton : CRC Press, 2023 9781032034041 (DLC) 2022055385 |
| ISBN |
9781003187158 (ebook) |
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1003187153 |
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9781000878875 (electronic bk. : PDF) |
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1000878872 (electronic bk. : PDF) |
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9781000878899 (electronic bk. : EPUB) |
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1000878899 (electronic bk. : EPUB) |
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(hardback) |
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(paperback) |
| Standard No. |
10.1201/9781003187158 doi |
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